Papers:
If you are a potential student and would like to get a better idea of what I do, here is a curated list of Introductory Papers, which might be more approachable than simply reading random papers off this list.
Note: Author order for all papers is either alphabetical or randomized.
Books:
Publications:
- Daniel Kane, Andreas Fackler, Adam Gągol, Damian Straszak, Highway: Efficient Consensus with Flexible Finality, in preparation.
- Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan Do PAC-Learners Learn the Marginal Distribution?, in preparation.
- Ilias Diakonikolas, Daniel M. Kane Efficiently Learning One-Hidden-Layer ReLU Networks via Schur Polynomials, in preparation.
- Yuqian Cheng, Daniel M. Kane, Zhicheng Zheng New Lower Bounds for Testing Monotonicity and Log Concavity of Distributions, in preparation.
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis Efficient Testable Learning of Halfspaces with Adversarial Label Noise, Advances in Neural Information Processing Systems (NeurIPS) 2023.
- Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise, Advances in Neural Information Processing Systems (NeurIPS) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Ankit Pensia, Thanasis Pittas A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm, Advances in Neural Information Processing Systems (NeurIPS) 2023 (spotlight presentation).
- Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis SQ Lower Bounds for Learning Bounded Covariance GMMs, Conference on
Learning Theory (COLT) 2023.
- Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise, Conference on
Learning Theory (COLT) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Yuetian Luo, Anru R. Zhang Statistical and Computational Limits for Tensor-on-Tensor Association Detection, Conference on
Learning Theory (COLT) 2023.
- Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan, Csaba Szepesvári, Gellért Weisz Exponential Hardness of Reinforcement Learning with Linear Function Approximation, Conference on
Learning Theory (COLT) 2023.
- Daniel M. Kane, Ilias Diakonikolas A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points, Conference on
Learning Theory (COLT) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals, International Conference on Machine Learning (ICML) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA, International Conference on Machine Learning (ICML) 2023.
- Ilias Diakonikolas, Christos Tzamos, Daniel Kane A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning, Symposium on Theory of Computation (STOC) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia Gaussian Mean Testing Made Simple, Symposium on Simplicity in Algorithms (SOSA 2023).
- Daniel Beaglehole, Max Hopkins, Daniel Kane, Sihan Liu, Shachar Lovett Sampling Equilibria: Fast No-Regret Learning in Structured Games, Symposium on Discrete
Algorithms (SODA) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren, Yuxin Sun SQ Lower Bounds for Learning Single Neurons with Massart Noise, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Sihan Liu Near-Optimal Bounds for Testing Histogram Distributions, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi, Lisheng Ren Cryptographic Hardness of Learning Halfspaces with Massart Noise, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Rong Ge, Shivam Gupta, Mahdi Soltanolkotabi Outlier-Robust Sparse Estimation via Non-Convex Optimization, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering, Advances in Neural Information Processing Systems (NeurIPS) 2022 (oral presentation).
- Daniel M. Kane Asymptotic Results for the
Queen Packing Problem, submitted to Journal
of Combinatorics.
- Ryan O'Donnell, Rocco A. Servedio, Li-Yang Tan with appendix by Daniel Kane Fooling Gaussian PTFs via Local Hyperconcentration, Journal of the ACM, to appear.
- Ilias Diakonikolas, Daniel M. Kane, Jasper C.H. Lee, Ankit Pensia Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Jeffery S. Cohen, Daniel M. Kane Bounds on the
Independence Required for Cuckoo Hashing, manuscript.
- Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas Robust Sparse Mean Estimation via Sum of Squares, Conference on Learning Theory (COLT) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun, Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models, Conference on Learning Theory (COLT) 2022.
- Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan Realizable Learning is All You Need, Conference on Learning Theory (COLT) 2022.
- Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan Computational-Statistical Gaps in Reinforcement Learning, Conference on Learning Theory (COLT) 2022.
- Ilias Diakonikolas, Daniel M. Kane Non-Gaussian Component Analysis via Lattice Basis Reduction, Conference on Learning Theory (COLT) 2022.
- Ilias Diakonikolas, Daniel M. Kane Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise, Conference on Learning Theory (COLT) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas Streaming Algorithms for High-Dimensional Robust Statistics, International Conference on Machine Learning (ICML) 2022.
- Daniel M. Kane, Shahed Sharif, Alice Silverberg Quantum Money from Quaternion Algebras, MathCrypt 2022.
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis Learning General Halfspaces with General Massart Noise under the Gaussian Distribution, Symposium on Theory of Computation (STOC) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian, Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation, Symposium on Theory of Computation (STOC) 2022.
- Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala, Robustly Learning Mixtures of k Arbitrary Gaussians, Symposium on Theory of Computation (STOC) 2022.
- Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren Hardness of Learning a Single Neuron with Adversarial Label Noise International Conference on Artificial Intelligence and Statistics (AISTATS) 2022 (oral presentation).
- Alaa Maalouf, Murad Tukan, Eric Price, Daniel Kane, Dan Feldman Coresets for Data Discretization and Sine Wave Fitting, Conference on Artificial Intelligence and Statistics (AISTATS) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas, Alistair Stewart Statistical Query Lower Bounds for List-Decodable Linear Regression, Conference on Neural Information Processing Systems (NeurIPS) 2021, spotlight presentation.
- Ilias Diakonikolas, Daniel M. Kane, Christos Tzamos Forster Decomposition and Learning Halfspaces with Noise, Conference on Neural Information Processing Systems (NeurIPS) 2021, spotlight presentation.
- Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian, List-Decodable Mean Estimation in Nearly-PCA Time, Advances in Neural Information Processing Systems (NeurIPS) 2021, spotlight presentation.
- Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz Bounded Memory Active Learning through Enriched Queries Conference on Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis Agnostic Proper Learning of Halfspaces under Gaussian Marginals Conference on Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals Conference on Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart, Yuxin Sun Outlier-Robust Learning of Ising Models Under Dobrushin’s Condition Conference on Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Russell Impagliazzo, Daniel Kane, Rex Lei, Jessica Sorrell, Christos Tzamos Boosting in the Presence of Massart Noise Conference on Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Daniel M. Kane, The Sample Complexity of Robust Covariance Testing, Conference on Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, John Peebles, Eric Price, Optimal Testing of Discrete Distributions with High Probability, Symposium on Theory of Computation (STOC) 2021.
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis, A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise, Symposium on Theory of Computation (STOC) 2021.
- Yuval Dagan, Yuval Filmus, Daniel Kane, Shay Moran The entropy of lies: playing twenty questions with a liar, Innovations in Theoretical Computer Science (ITCS) 2021.
- Ilias Diakonikolas, Gautam Kamath, Daniel M Kane, Jerry Li, Ankur Moitra, Alistair Stewart Robustness Meets Algorithms, Communications of the ACM Vol 64(5) p. 107-115, 2001.
- Daniel M. Kane, Scott Duke Kominers Prisoners, Rooms, and Lightswitches, Electronic Journal of Combinatorics, Vol 28 (1), 2021 pp. 1-27.
- Daniel M. Kane Robust Learning of Mixtures of Gaussians, Symposium On Discrete Algorithms (SODA) 2021.
- Ilias Diakonikolas, Samuel B. Hopkins, Daniel Kane, Sushrut Karmalkar Robustly Learning any Clusterable Mixture of Gaussians, Foundations
Of Computer Science (FOCS) 2020.
- Ilias Diakonikolas, Daniel M. Kane Small Covers for Near-zero Sets of Polynomials and Learning Latent Variable Models, Foundations
Of Computer Science (FOCS) 2020.
- Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan, Point Location and Active Learning: Learning Halfspaces Almost Optimally, Foundations
Of Computer Science (FOCS) 2020.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia Outlier Robust Mean Estimation with Subgaussian Rates via Stability, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Ilias Diakonikolas, Daniel M. Kane, Nikos Zarifis Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard List-Decodable Mean Estimation via Iterative Multi-Fitering, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Max Hopkins, Daniel Kane, Shachar Lovett, The Power of Comparisons for Actively Learning Linear Classifiers, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Venkata Gandikota, Daniel Kane, Raj Kumar Maity, Arya Mazumdar Vector Quantized Stochastic Gradient Descent, 54th Asilomar Conference on Signals, Systems and Computers (Asilomar) 2020, journal version in IEEE Transactions on Information Theory, 2022.
- Ilias Diakonikolas, Daniel Kane, Vasileios Kontonis, Nikos Zarifis Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks Conference On Learning Theory (COLT) 2020.
- Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan Noise-tolerant, Reliable Active Classification with Comparison Queries, Conference On Learning Theory (COLT) 2020.
- Ilias Diakonikolas, Daniel M. Kane Recent Advances in Algorithmic High-Dimensional Robust Statistics, shortened version in Tim Roughgarden's Beyond Worst Case Analysis book.
- Daniel M. Kane, Carlo Sanna, Jeffrey Shallit Waring's Theorem for Binary Powers, Combinatorica Vol 39 (2019) pp. 1335-1350.
- M. Aliakbarpour, I. Diakonikolas, D. Kane, R. Rubinfeld Private Testing of Distributions via Sample Permutations, Advances in Neural Information Processing Systems (NeurIPS) 2019.
- Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin, Advances in Neural Information Processing Systems (NeurIPS) 2019 (Spotlight Presentation).
- Ilias Diakonikolas, Sushrut Karmalkar, Daniel Kane, Eric Price, Alistair Stewart Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering, Advances in Neural Information Processing Systems (NeurIPS) 2019.
- Daniel M Kane, Roi Livni, Shay Moran, Amir Yehudayoff On Communication Complexity of Classification Problems, Conference on
Learning Theory (COLT) 2019.
- Surbhi Goel, Daniel M. Kane, Adam R. Klivans Learning Ising Models with Independent Failures, Conference on
Learning Theory (COLT) 2019.
- Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, Sankeerth Rao, Communication and Memory Efficient Testing of Discrete Distributions, Conference on
Learning Theory (COLT) 2019.
- Olivier Bousquet, Daniel Kane, Shay Moran The Optimal Approximation Factor in Density Estimation, Conference on
Learning Theory (COLT) 2019.
- Ilias Diakonikolas, Daniel M. Kane, John Peebles Testing Identity of Multidimensional Histograms, Conference on
Learning Theory (COLT) 2019.
- Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart Sever: A Robust Meta-Algorithm for Stochastic Optimization, International
Conference on Machine Learning (ICML) 2019.
- Ilias Diakonikolas, Daniel M. Kane, Degree-d Chow Parameters Robustly Determine Degree-d PTFs (and Algorithmic Applications) Symposium on Theory Of Computation (STOC) 2019.
- Daniel M Kane, Ryan Williams The Orthogonal Vectors Conjecture for Branching Programs and Formulas, Innovations in Theoretical Computer Science (ITCS) 2019.
- Daniel M. Kane, Robert C. Rhoades A Proof of Andrews' Conjecture
on Partitions with no Short Sequences, Forum of Mathematics
Sigma, Vol 7, 2019.
- Ben Green, Daniel M. Kane, An
Example Concerning Set Addition in F_2^n, Trudy Matematicheskogo Instituta im. V.A. Steklova Vol 303 (2018) pp. 116-119.
- Ilias Diakonikolas, Daniel M Kane, Alistair Stewart Sharp Bounds for Generalized Uniformity Testing, Advances in Neural Information Processing Systems (NeurIPS) 2018, Spotlight Presentation at NeurIPS 2018.
- Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart Robust
Learning of Fixed-Structure Bayesian Networks, Neural Information Processing Systems (NIPS) 2018.
- Daniel M Kane, Shachar Lovett, Shay Moran Generalized Comparison Trees for Point-Location Problems, International Colloquium on Automata, Languages and Programming
(ICALP) 2018.
- Ilias Diakonikolas, Daniel M Kane, Alistair Stewart Learning Geometric Concepts with Nasty Noise, Symposium on Theory Of Computation (STOC) 2018.
- Clement Canonne, Ilias Diakonikolas, Daniel M.
Kane, Alistair Stewart Testing Conditional Independence of Discrete Distributions, Symposium on Theory Of Computation (STOC) 2018.
- Ilias Diakonikolas, Daniel M.
Kane, Alistair Stewart List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians, Symposium on Theory Of Computation (STOC) 2018.
- Daniel M Kane, Shachar Lovett, Shay Moran Near-Optimal Linear Decision
Trees for k-SUM and Related Problems, Symposium on Theory Of Computation (STOC) 2018, invited to STOC special issue, Journal of the ACM, Vol 66, no 3 (2019).
- Daniel M Kane, Sankeerth Rao A PRG for Boolean PTF of Degree 2 with Seed Length Subpolynomial in ε and Logarithmic in n, Conference on Computational Complexity (CCC) 2018.
- Ilias Diakonikolas, Gautam Kamath, Daniel M.
Kane, Jerry Li, Ankur Moitra, Alistair Stewart Robustly Learning a Gaussian: Getting Optimal Error Efficiently, Symposium On Discrete Algorithms (SODA) 2018.
- Daniel M. Kane, Joseph Palmer, Alvaro Pelayo Minimal Models of Compact
Symplectic Semiotic Manifolds, Journal of Geometry and Physics, Vol 125 (2018) pp. 48-74.
- Daniel M. Kane,
Joseph Palmer, Alvaro Pelayo Classifying Toric and Semitoric Fans by Lifting Equations from SL2(Z), SIGMA Vol 14 (2018).
- Daniel M. Kane, Zev Klagsbrun, On the Joint Distribution
Of Selφ(E/Q) and Selφ^(E/Q) in
Quadratic Twist Families, manuscript.
- Daniel Kane, Sushrut Karmalkar, Eric Price Robust
Polynomial Regression up to the Information Theoretic Limit, Foundations of Computer Science (FOCS)
2017.
- Daniel M. Kane, Shachar Lovett, Shay Moran,
Jiapeng Zhang, Active
Classification with Comparison Queries, Foundations
Of Computer Science (FOCS) 2017.
- Daniel M Kane, Shachar Lovett, Sankeerth Rao, The Independence Number
of the Birkhoff Polytope Graph and Applications to Maximally Recoverable Codes,
Foundations Of Computer Science
(FOCS) 2017, journal version SIAM Journal of computing (SICOMP) Vol 48, no 4 (2019) pp 1425-1435.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart Statistical
Query Lower Bounds for Robust Estimation of High Dimensional Gaussians and
Gaussian Mixtures, Foundations Of
Computer Science (FOCS) 2017.
- Ilias Diakonikolas, Daniel M. Kane, Vladimir
Nikishkin Near-Optimal
Closeness Testing of Discrete Histogram Distributions, International Colloquium on Automata, Languages and Programming
(ICALP) 2017.
- Ilias Diakonikolas, Gautam Kamath, Daniel M.
Kane, Jerry Li, Ankur Moitra, Alistair Stewart Being Robust in High
Dimensions Can Be Practical, International
Conference on Machine Learning (ICML) 2017.
- Clement Canonne, Ilias Diakonikolas, Daniel M.
Kane, Alistair Stewart Testing
Bayesian Networks, Conference on
Learning Theory (COLT) 2017; Journal version in IEEE Transactions on Information Theory pp. 1-39, 2020.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart Learning
Multivariate Log-concave Distributions, Conference
On Learning Theory (COLT) 2017.
- Valentine Kabanets, Daniel M. Kane, Zhenjian Lu A Polynomial
Restriction Lemma with Applications, Symposium
on Theory Of Computation (STOC) 2017.
- Daniel M. Kane, Terence Tao A Bound on
Partitioning Clusters, Electronic
Journal of Combinatorics Vol 24 no 2 (2017) #P2.31.
- Daniel M. Kane On the Crossing
Number of Complete Graphs with an Uncrossed Hamiltonian Cycle, manuscript.
- Daniel M. Kane, Jack A. Thorne, On
the φ-Selmer Groups of Elliptic Curves y2 = x3 – Dx, Mathematical
Proceedings of the Cambridge Philosophical Society, Vol 163 no 1 (2017) pp. 1–23.
- Chung-Kuan Cheng, Daniel
M. Kane, Ilgweon Kang, Fang Qiao, 3D Floorplan
Representations: Corner Links and Partial Ordering, IEEE International 3D Systems Integration
Conference (3DIC) 2016, Journal Version: Kang, I., Qiao, F., Park, D., Kane, D., Young, E.F.Y., Cheng, C.K., Graham, R. Three-dimensional Floorplan Representations by Using Corner Links and Partial Order ACM Transactions on Design Automation of Electronic Systems (TODAES), 24(1), p.13, 2018.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart Efficient
Robust Proper Learning of Log-concave Distributions, manuscript.
- Xue Chen, Daniel M. Kane, Eric Price, Zhao Song,
Fourier-sparse
interpolation without a frequency gap, Foundations
Of Computer Science, (FOCS) 2016.
- Ilias Diakonikolas, Gautam Kamath, Daniel M.
Kane, Jerry Li, Ankur Moitra, Alistair Stewart, Robust Estimators
in High Dimensions without the Computational Intractability, Foundations Of Computer Science, (FOCS)
2016, journal version in SIAM Journal of computing (SICOMP) Vol 48, no 2 (2019), pp. 742-864.
- Ilias Diakonikolas, Daniel M. Kane, A
New Approach for Testing Properties of Discrete Distributions, Foundations Of Computer Science, (FOCS)
2016.
- Mihir Bellare, Daniel M. Kane, Phillip Rogaway Big-Key Symmetric Encryption:
Resisting Key Exfiltration, International
Cryptography Conference (CRYPTO) 2016.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart, Nearly Optimal
Learning and Sparse Covers for Sums of Independent Integer Random Variables,
Conference On
Learning Theory, (COLT) 2016.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart, Properly
Learning Poisson Binomial Distributions in Almost Polynomial Time, Conference On
Learning Theory, (COLT) 2016.
- Daniel M. Kane, Ryan Williams, Super-Linear Gate and
Super-Quadratic Wire Lower Bounds for Depth-Two and Depth-Three Threshold
Circuits, Symposium on the Theory of
Computation (STOC) 2016.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart The Fourier
Transform of Poisson Multinomial Distributions and its Algorithmic Applications,
Symposium on the Theory of Computation (STOC)
2016.
- Mihir Bellare, Joseph Jaeger, Daniel Kane, Mass-surveillance
without the State: Strongly Undetectable Algorithm-Substitution Attacks on
Symmetric Encryption, Conference
on Computer and Communications Security (CCS) 2016.
- Daniel M. Kane On the
Number of ABC Solutions with Restricted Radical Sizes, Journal of Number
Theory, (2015), pp. 32-43.
- Daniel M. Kane Small Designs for Path
Connected Spaces and Path Connected Homogeneous Spaces, Transactions of the AMS, Vol. 367
(2015), pp. 6387-6414.
- Daniel M. Kane Canonical Projective
Embeddings of the Deligne-Lusztig Curves Associated to 2A2,
2B2 and 2G2, International Mathematics Research Notices,
(2015) pp. 1158-1189.
- Manjul Bhargava, Daniel M. Kane, Hendrik W.
Lenstra Jr., Bjorn Poonen, Eric Rains Modeling the Distribution of
Ranks, Selmer Groups, and Shafarevich-Tate Groups of Elliptic Curves, Cambridge Journal of Mathematics, Vol. 3
(2015), pp. 275-321.
- Bobbie Chern, Persi Diaconis, Daniel M. Kane,
Robert C. Rhoades Central Limit
Theorems for Some Set Partition Statistics, Advances in Applied Mathematics, Vol. 70 (2015), pp. 92–105.
- Andrew Granville, Daniel M Kane, Dimitris Koukoulopoulos, Robert J Lemke Oliver Best Possible Densities of Dickson m-Tuples, as a Consequence of Zhang–Maynard–Tao in Analytic Number Theory Springer, 2015.
- Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin, Optimal
Algorithms and Lower Bounds for Testing Closeness of Structured Distributions,
Foundations of Computer Science,
(FOCS) 2015.
- Parikshit Gopalan, Daniel M. Kane, Raghu Meka, Pseudorandomness via the
Discrete Fourier Transform, Foundations
of Computer Science (FOCS) 2015, SIAM Journal of computing (SICOMP) Vol 47, no 6 pp. 2451-2487.
- Daniel M. Kane A Polylogarthmic PRG for
Degree 2 Threshold Functions in the Gaussian Setting, Conference on Computational Complexity (CCC) 2015.
- Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin, Testing Identity of Structured
Distributions, Symposium On Discrete Algorithms (SODA) 2015.
- Daniel M. Kane, Osamu Watanabe A Short Implicant of CNFs with
a Relatively Many Satisfying Assignments, International Symposium on Algorithms And Computation (ISAAC) 2014;
journal version Algorithmica, (2016),
DOI: 10.1007/s00453-016-0125-z.
- Daniel M. Kane The Average Sensitivity
of an Intersection of Half Spaces, Symposium
on the Theory Of Computing 2014, journal
version (open access) in Research In
the Mathematical Sciences Vol. 1 no 1 (2014).
- Daniel M. Kane A Pseudorandom Generator
for Polynomial Threshold Functions of Gaussians with Subpolynomial Seed Length,
Conference on Computational Complexity
2014.
- Bobbie Chern, Persi Diaconis, Daniel M. Kane,
Robert C. Rhoades Closed
Expressions for Averages of Set Partition Statistics, Research in the Mathematical Sciences, Vol. 1 (2014) no. 2.
- Daniel M. Kane, Scott Duke Kominers Asymptotic Improvements of
Lower Bounds for the Least Common Multiples of Arithmetic Progressions, Canadian Mathematical Bulletin, Vol. 57
(2014), pp. 551-561.
- Daniel M. Kane, Adam Klivans, Raghu Meka Learning Half Spaces Under
Log-Concave Densities: Polynomial Approximation and Moment Matching, Conference on Learning Theory (COLT) 2013.
- Daniel M. Kane The Correct Exponent for
the Gotsman-Linial Conjecture, Conference
on Computational Complexity (CCC) 2013 (won best paper award).
- Daniel
M. Kane, Raghu Meka A PRG
for Lipschitz Functions of Polynomials with Applications to Sparsest Cut, Symposium on the Theory of Computation (STOC) 2013.
- Daniel M. Kane A Low-Depth
Monotone Function Given by a Low-Depth Decision Tree
that is not an Approximate Junta, Theory
of Computing Vol. 9 (2013) pp. 587-592.
- Noam D. Elkies, Daniel M. Kane, Scott Duke
Kominers, Minimal
S-Criteria May Vary in Size, Journal de Theorie des Nombres de Bordeaux, Vol. 23 no. 3 (2013) pp. 557-563.
- Daniel M. Kane On
the Ranks of the 2-Selmer Groups of Twists of a Given Elliptic Curve, Algebra & Number Theory, 7 issue 5 (2013),
pp. 1253-1297.
- Daniel M. Kane An Asymptotic for the
Number of Solutions to Linear Equations in Prime Numbers from Specified Chebotarev
Classes, International Journal of Number Theory, Vol. 9 no. 4 (2013) pp. 1073-1111.
- Daniel M. Kane A Structure
Theorem for Poorly Anticoncentrated Gaussian Chaoses and Applications to the
Study of Polynomial Threshold Functions, Foundations of Computer Science (FOCS) 2012, pp. 91-100; journal
version Annals of Probability, Vol. 45 no. 3 (2017) pp. 1612-1679.
- Daniel M. Kane, Kurt Mehlhorn, Thomas Sauerwald,
He Sun Counting
Arbitrary Subgraphs in Data Streams, International
Colloquium on Automata, Languages and Programming (ICALP) 2012, pp. 598-609.
- Eric Blais, Daniel Kane Tight Bounds
for Testing k-Linearity, International
Workshop on Randomization and Computation (RANDOM) 2012.
- Daniel M. Kane, Jelani Nelson, Sparser
Johnson-Lindenstrauss Transforms, Symposium
on Discrete Algorithms (SODA) 2012, Journal of the ACM, Vol. 61 no. 1,
Article 4, 2014.
- Daniel M. Kane, A
Small PRG for Polynomial Threshold Functions of Gaussians, Foundations of Computer Science (FOCS)
2011.
- Daniel M. Kane, Raghu Meka, Jelani Nelson, Almost Optimal
Explicit Johnson-Lindenstrauss Transforms, International Workshop on Randomization and Computation (RANDOM), 2011.
- Daniel Kane, Jelani Nelson, A Derandomized Sparse
Johnson-Lindenstrauss Transform, superseded by Sparser
Johnson-Lindenstrauss Transforms (above).
- Daniel M. Kane k-Independent Gaussians
Fool Polynomial Threshold Functions, Conference
on Computational Complexity (CCC), 2011.
- Daniel M. Kane, Jelani Nelson, Ely Porat,
David P. Woodruff, Fast
Moment Estimation in Data Streams in Optimal Space, Symposium on the
Theory of Computing (STOC) 2011.
- Daniel M. Kane, Samuel A. Kutin, Quantum
Interpolation of Polynomials, presented at Combinatorics, Groups, Algorithms, and Complexity (conference in honor
of Laci Babai’s 60th birthday (CGAC) 2010, journal version in Quantum Information and Computation Vol.
11 no. 1&2 (2011).
- Daniel M. Kane Unary Subset-Sum is in
Logspace, unpublished.
- Ilias Diakonikolas, Daniel M. Kane, Jelani
Nelson, Bounded
Independence Fools Degree-2 Threshold Functions, Foundations of Computer Science (FOCS) 2010.
- Daniel M. Kane The
Gaussian Surface Area and Noise Sensitivity of Degree-d Polynomial Threshold
Functions, in Conference on
Computational Complexity (CCC) 2010, pp. 205-210 (Won CCC 2010 best student
paper).
- Daniel M. Kane, Jelani Nelson, David P. Woodruff
An Optimal Algorithm
for the Distinct Elements Problem, Symposium
on Principles of Database Systems (PODS) 2010 (Won PODS 2010 best paper,
and 2010 IBM research Pat Goldberg Memorial Best Paper Award in Computer
Science, Electrical Engineering and Math). Invited
to Journal of the ACM.
- Daniel M. Kane, Jelani Nelson, David P. Woodruff
On the Exact Space
Complexity of Sketching and Streaming Small Norms, Proceedings of the 21st Annual ACM-SIAM Symposium on Discrete
Algorithms (SODA) 2010.
- Chris Dodd, Phakawa Jeasakul, Anne
Jirapattanakul, Daniel M. Kane, Becky Robinson, Noah Stein, Cesar E. Silva Ergodic Properties of a Class
of Discrete Abelian Group Extensions of Rank-One Transformations, Colloquium Mathematicum, 119 (2010), pp.
1-22.
- Daniel M. Kane On Solving Games
Constructed Using Both Shortened and Continued Conjunctive Sums, Integers: Electronic Journal of
Combinatorial Number Theory, 10 (2010), pp. 849-878.
- Daniel M. Kane A
Partition of the Positive Reals into Algebraically Closed Subsets,
unpublished.
- Erik D. Demaine, Dion Harmon, John Iacono,
Daniel M. Kane, Mihai Pǎtraşcu, The Geometry of Binary
Search Trees, in Symposium on
Discrete Algorithms (SODA) 2009.
- Daniel M. Kane, Gregory N. Price, Erik D.
Demaine, A
Pseudopolynomial Algorithm for Alexandrov's Theorem, Algorithms and Data Structures Symposium (WADS) 2009. Also in Lecture
Notes in Computer Science, 5664 (2009) pp. 435–446.
- Bakir Farhi, Daniel Kane New Results on the Least Common
Multiple of Consecutive Integers, Proceedings
of the AMS, 137 (2009), no. 6, pp. 1933-1939.
- Daniel Kane, Steven Sivek On the Sn-Modules
Generated by Partitions of a Given Shape, The Electronic Journal of Combinatorics, 15 (2008), 12 pages.
- Daniel M. Kane On
Lower Bounds on the Size of Sums-of-Squares Formulas Journal of Number
Theory, 128 (2008) pp. 639-644.
- Daniel M. Kane Improved Bounds on the
Number of Ways of Expressing t as a
Binomial Coefficient, Integers:
Electronic Journal of Combinatorial Number Theory, Vol. 7 (2007), #A53 pp.
1-7.
- Dan Gulotta, Daniel M. Kane, Andrew Spann Electoral Redistricting with
Moment of Inertia and Diminishing Halves Models(3.81 MB) UMAP Journal, Vol. 28 (2007), pp.
281-299
- Daniel M. Kane Weak Mixing of a
Transformation Similar to Pascal, Colloquium Mathematicum,
Vol. 108 no. 1(2007), pp. 135-140.
- Daniel M. Kane Asymptotics of McKay
Numbers for Sn, Journal of Number Theory, Vol. 124 (2007) pp.
200-228.
- Dan Gulotta, Daniel M. Kane, Andrew Spann Application of Min-Cost Flow
to Airline Accessibility Services UMAP Journal, Vol. 27 (2006), pp.
367-385.
- Daniel M. Kane Generalized
Base Representations Journal of Number Theory, Vol. 120 (2006) pp. 92-100.
- Daniel M. Kane, Jonathan M. Kane Dropping Lowest Grades
Mathematics Magazine, Vol. 79 (June 2006) pp. 181-189.
- Daniel M. Kane An
Elementary Derivation of the Asymptotics of Partition Functions The
Ramanujan Journal, Vol. 11 no. 1(2006) pp. 49-66.
- Tim G. Abbott, Daniel M. Kane, Paul Valiant On the
Complexity of Two-Player Win-Lose Games Foundations Of Computer Science (FOCS) 2005 (Won
Machtey award for best student paper).
- Timothy G. Abbott, Michael A. Burr, Timothy M.
Chan, Erik D. Demaine, Martin L. Demaine, John Hugg, Daniel Kane, Stefan
Langerman, Jelani Nelson, Eynat Rafalin, Kathryn Seyboth, Vincent Yeung, Dynamic
Ham-Sandwich Cuts in the Plane, Computational
Geometry: Theory and Applications, Vol. 42, no. 5, July 2009, pages
419–428. Special issue of selected papers
from the 17th Canadian Conference on Computational Geometry, 2005.
- Tim Abbott, Erik D. Demaine, Martin L. Demaine,
Daniel M. Kane, Setfan Langerman, Jelani Nelson, Vincent Yeung Dynamic Ham-Sandwich
Cuts of Polygons in the Plane Canadian
Conference on Computational Geometry, (2005) pp. 61-64.
- Dan Gulotta, Daniel M. Kane, Andrew Spann Lane Changes and Close
Following: Troublesome Tollbooth Traffic(6 MB) UMAP
Journal, Vol. 26 no. 3 (2005) pp. 251-264.
- Daniel M. Kane On the Number of Ways of
Writing t as a Product of Factorials Integers: Electronic Journal of
Combinatorial Number Theory, Vol. 5 (2005), #A02, pp. 1-10.
- Daniel M. Kane Resolution of a
Conjecture Involving Cranks of Partitions of Andrews and Lewis Proceedings
of the American Mathematical Society, Vol. 132 No. 8(2004), pp. 2247-2256.
-
Daniel M. Kane New Bounds on the
Number of Representations of t as a Binomial Coefficient Integers: Electronic Journal of
Combinatorial Number Theory, Vol. 4 (2004), #A07, pp. 1-10.
By Topic:
- Computer Science:
- Learning Theory:
- Robust Statistics:
- Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Ankit Pensia, Thanasis Pittas A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm, Advances in Neural Information Processing Systems (NeurIPS) 2023 (spotlight presentation).
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA, International Conference on Machine Learning (ICML) 2023.
- Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Rong Ge, Shivam Gupta, Mahdi Soltanolkotabi Outlier-Robust Sparse Estimation via Non-Convex Optimization, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering, Advances in Neural Information Processing Systems (NeurIPS) 2022 (oral presentation).
- Ilias Diakonikolas, Daniel M. Kane, Jasper C.H. Lee, Ankit Pensia Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas Robust Sparse Mean Estimation via Sum of Squares, Conference on Learning Theory (COLT) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun, Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models, Conference on Learning Theory (COLT) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas Streaming Algorithms for High-Dimensional Robust Statistics, International Conference on Machine Learning (ICML) 2022.
- Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala, Robustly Learning Mixtures of k Arbitrary Gaussians, Symposium on Theory of Computation (STOC) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation, Symposium on Theory of Computation (STOC) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas, Alistair Stewart Statistical Query Lower Bounds for List-Decodable Linear Regression, Conference on Neural Information Processing Systems (NeurIPS) 2021, spotlight presentation.
- Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart, Yuxin Sun Outlier-Robust Learning of Ising Models Under Dobrushin’s Condition, Conference on
Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Daniel M. Kane, The Sample Complexity of Robust Covariance Testing, Conference on
Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Gautam Kamath, Daniel M Kane, Jerry Li, Ankur Moitra, Alistair Stewart Robustness Meets Algorithms, Communications of the ACM Vol 64(5) p. 107-115, 2001.
- Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian, List-Decodable Mean Estimation in Nearly-PCA Time, Advances in Neural Information Processing Systems (NeurIPS) 2021, spotlight presentation.
- Daniel M. Kane Robust Learning of Mixtures of Gaussians, Symposium On Discrete Algorithms (SODA) 2021.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia Outlier Robust Mean Estimation with Subgaussian Rates via Stability, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Ilias Diakonikolas, Daniel M. Kane, Nikos Zarifis Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard List-Decodable Mean Estimation via Iterative Multi-Fitering, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Ilias Diakonikolas, Samuel B. Hopkins, Daniel Kane, Sushrut Karmalkar Robustly Learning any Clusterable Mixture of Gaussians, Foundations
Of Computer Science (FOCS) 2020.
- Ilias Diakonikolas, Daniel M. Kane Recent Advances in Algorithmic High-Dimensional Robust Statistics, shortened version in Tim Roughgarden's Beyond Worst Case Analysis book.
- Ilias Diakonikolas, Sushrut Karmalkar, Daniel Kane, Eric Price, Alistair Stewart Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering, Advances in Neural Information Processing Systems (NeurIPS 2019).
- Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart Sever: A Robust Meta-Algorithm for Stochastic Optimization, International
Conference on Machine Learning (ICML) 2019.
- Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart Robust
Learning of Fixed-Structure Bayesian Networks, Neural Information Processing Systems (NIPS) 2018.
- Ilias Diakonikolas, Daniel M Kane, Alistair Stewart Learning Geometric Concepts with Nasty Noise, Symposium on Theory Of Computation (STOC) 2018.
- Ilias Diakonikolas, Daniel M.
Kane, Alistair Stewart List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians, Symposium on Theory Of Computation (STOC) 2018.
- Ilias Diakonikolas, Gautam Kamath, Daniel M.
Kane, Jerry Li, Ankur Moitra, Alistair Stewart Robustly Learning a Gaussian: Getting Optimal Error Efficiently, Symposium On Discrete Algorithms (SODA) 2018.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart Statistical
Query Lower Bounds for Robust Estimation of High Dimensional Gaussians and
Gaussian Mixtures, Foundations Of
Computer Science (FOCS) 2017.
- Ilias Diakonikolas, Gautam Kamath, Daniel M.
Kane, Jerry Li, Ankur Moitra, Alistair Stewart Being Robust in High
Dimensions Can Be Practical, International
Conference on Machine Learning (ICML) 2017.
- Ilias Diakonikolas, Gautam Kamath, Daniel M.
Kane, Jerry Li, Ankur Moitra, Alistair Stewart, Robust Estimators
in High Dimensions without the Computational Intractability, Foundations Of Computer Science, (FOCS)
2016, journal version in SIAM Journal of computing (SICOMP) Vol 48, no 2 (2019), pp. 742-864.
- Testing Discrete Distributions:
- Yuqian Cheng, Daniel M. Kane, Zhicheng Zheng New Lower Bounds for Testing Monotonicity and Log Concavity of Distributions, in preparation.
- Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Sihan Liu Near-Optimal Bounds for Testing Histogram Distributions, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, John Peebles, Eric Price, Optimal Testing of Discrete Distributions with High Probability, Symposium on Theory of Computation (STOC) 2021.
- M. Aliakbarpour, I. Diakonikolas, D. Kane, R. Rubinfeld Private Testing of Distributions via Sample Permutations, Advances in Neural Information Processing Systems (NeurIPS 2019).
- Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, Sankeerth Rao, Communication and Memory Efficient Testing of Discrete Distributions, Conference on
Learning Theory (COLT) 2019.
- Ilias Diakonikolas, Daniel M Kane, Alistair Stewart Sharp Bounds for Generalized Uniformity Testing, Advances in Neural Information Processing Systems (NeurIPS) 2018, Spotlight Presentation at NeurIPS 2018.
- Clement Canonne, Ilias Diakonikolas, Daniel M.
Kane, Alistair Stewart Testing Conditional Independence of Discrete Distributions, Symposium on Theory Of Computation (STOC) 2018.
- Ilias Diakonikolas, Daniel M. Kane, A
New Approach for Testing Properties of Discrete Distributions, Foundations Of Computer Science, (FOCS)
2016.
- Structured Learning/Testing Problems:
- Ilias Diakonikolas, Daniel M. Kane Efficiently Learning One-Hidden-Layer ReLU Networks via Schur Polynomials, in preparation.
- Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis SQ Lower Bounds for Learning Bounded Covariance GMMs, Conference on
Learning Theory (COLT) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Yuetian Luo, Anru R. Zhang Statistical and Computational Limits for Tensor-on-Tensor Association Detection, Conference on
Learning Theory (COLT) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia Gaussian Mean Testing Made Simple, Symposium on Simplicity in Algorithms (SOSA 2023).
- Ilias Diakonikolas, Daniel M. Kane, John Peebles Testing Identity of Multidimensional Histograms, Conference on
Learning Theory (COLT) 2019.
- Ilias Diakonikolas, Daniel M. Kane, Vladimir
Nikishkin Near-Optimal
Closeness Testing of Discrete Histogram Distributions, International Colloquium on Automata, Languages and Programming
(ICALP) 2017.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart, Nearly Optimal
Learning and Sparse Covers for Sums of Independent Integer Random Variables,
Conference On
Learning Theory, (COLT) 2016.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart, Properly
Learning Poisson Binomial Distributions in Almost Polynomial Time, Conference On
Learning Theory, (COLT) 2016.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart The Fourier
Transform of Poisson Multinomial Distributions and its Algorithmic Applications,
Symposium on the Theory of Computation (STOC)
2016.
- Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin, Optimal
Algorithms and Lower Bounds for Testing Closeness of Structured Distributions,
Foundations of Computer Science,
(FOCS) 2015.
- Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin, Testing Identity of Structured
Distributions, Symposium On Discrete Algorithms (SODA) 2015.
- Active Learning and Inference Dimension:
- Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz Bounded Memory Active Learning through Enriched Queries, Conference on
Learning Theory (COLT) 2021.
- Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan Point Location and Active Learning: Learning Halfspaces Almost Optimally, Foundations
Of Computer Science (FOCS) 2020.
- Max Hopkins, Daniel Kane, Shachar Lovett, The Power of Comparisons for Actively Learning Linear Classifiers, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan Noise-tolerant, Reliable Active Classification with Comparison Queries, Conference On Learning Theory (COLT) 2020.
- Daniel M Kane, Shachar Lovett, Shay Moran Generalized Comparison Trees for Point-Location Problems, International Colloquium on Automata, Languages and Programming
(ICALP) 2018.
- Daniel M Kane, Shachar Lovett, Shay Moran Near-Optimal Linear Decision
Trees for k-SUM and Related Problems, Symposium on Theory Of Computation (STOC) 2018, invited to STOC special issue, Journal of the ACM, Vol 66, no 3 (2019).
- Daniel M. Kane, Shachar Lovett, Shay Moran,
Jiapeng Zhang, Active
Classification with Comparison Queries Foundations
Of Computer Science (FOCS) 2017.
- Learning Functions:
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis Efficient Testable Learning of Halfspaces with Adversarial Label Noise, Advances in Neural Information Processing Systems (NeurIPS) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals, International Conference on Machine Learning (ICML) 2023.
- Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren Hardness of Learning a Single Neuron with Adversarial Label Noise International Conference on Artificial Intelligence and Statistics (AISTATS) 2022 (oral presentation).
- Ilias Diakonikolas, Daniel M. Kane, Christos Tzamos Forster Decomposition and Learning Halfspaces with Noise, Conference on Neural Information Processing Systems (NeurIPS) 2021, spotlight presentation.
- Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals, Conference on
Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis Agnostic Proper Learning of Halfspaces under Gaussian Marginals, Conference on
Learning Theory (COLT) 2021.
- Ilias Diakonikolas, Daniel M. Kane Small Covers for Near-zero Sets of Polynomials and Learning Latent Variable Models, Foundations
Of Computer Science (FOCS) 2020.
- Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise, Advances in Neural Information Processing Systems (NeurIPS) 2020.
- Ilias Diakonikolas, Daniel Kane, Vasileios Kontonis, Nikos Zarifis Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks Conference On Learning Theory (COLT) 2020.
- Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin, Advances in Neural Information Processing Systems (NeurIPS 2019) (Spotlight Presentation).
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis, A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise, Symposium on Theory of Computation (STOC) 2021.
- Daniel Kane, Sushrut Karmalkar, Eric Price Robust
Polynomial Regression up to the Information Theoretic Limit, Foundations of Computer Science (FOCS)
2017.
- Xue Chen, Daniel M. Kane, Eric Price, Zhao Song,
Fourier-sparse
interpolation without a frequency gap, Foundations
Of Computer Science, (FOCS) 2016.
- Semi-Random Noise Models:
- Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise, Advances in Neural Information Processing Systems (NeurIPS) 2023.
- Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise, Conference on
Learning Theory (COLT) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren, Yuxin Sun SQ Lower Bounds for Learning Single Neurons with Massart Noise, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi, Lisheng Ren Cryptographic Hardness of Learning Halfspaces with Massart Noise, Advances in Neural Information Processing Systems (NeurIPS) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise, Conference on Learning Theory (COLT) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis Learning General Halfspaces with General Massart Noise under the Gaussian Distribution, Symposium on Theory of Computation (STOC) 2022.
- Ilias Diakonikolas, Russell Impagliazzo, Daniel Kane, Rex Lei, Jessica Sorrell, Christos Tzamos Boosting in the Presence of Massart Noise, Conference on
Learning Theory (COLT) 2021.
- Other Learning Theory:
- Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan Do PAC-Learners Learn the Marginal Distribution?, in preparation.
- Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan, Csaba Szepesvári, Gellért Weisz Exponential Hardness of Reinforcement Learning with Linear Function Approximation, Conference on
Learning Theory (COLT) 2023.
- Ilias Diakonikolas, Christos Tzamos, Daniel Kane A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning, Symposium on Theory of Computation (STOC) 2023.
- Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan Computational-Statistical Gaps in Reinforcement Learning, in preparation.
- Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan Realizable Learning is All You Need, Conference on Learning Theory (COLT) 2022.
- Ilias Diakonikolas, Daniel M. Kane Non-Gaussian Component Analysis via Lattice Basis Reduction, Conference on Learning Theory (COLT) 2022.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart Efficient
Robust Proper Learning of Log-concave Distributions, manuscript.
- Yuval Dagan, Yuval Filmus, Daniel Kane, Shay Moran The entropy of lies: playing twenty questions with a liar, Innovations in Theoretical Computer Science (ITCS) 2021.
- Daniel M Kane, Roi Livni, Shay Moran, Amir Yehudayoff On Communication Complexity of Classification Problems, Conference on
Learning Theory (COLT) 2019.
- Surbhi Goel, Daniel M. Kane, Adam R. Klivans Learning Ising Models with Independent Failures, Conference on
Learning Theory (COLT) 2019.
- Olivier Bousquet, Daniel Kane, Shay Moran The Optimal Approximation Factor in Density Estimation, Conference on
Learning Theory (COLT) 2019.
- Clement Canonne, Ilias Diakonikolas, Daniel M.
Kane, Alistair Stewart Testing
Bayesian Networks, Conference on
Learning Theory (COLT) 2017; Journal version in IEEE Transactions on Information Theory pp. 1-39, 2020.
- Ilias Diakonikolas, Daniel M. Kane, Alistair
Stewart Learning
Multivariate Log-concave Distributions, Conference
On Learning Theory (COLT) 2017.
- Polynomial Threshold Functions:
- Ryan O'Donnell, Rocco A. Servedio, Li-Yang Tan with appendix by Daniel Kane Fooling Gaussian PTFs via Local Hyperconcentration, Journal of the ACM, to appear.
- Ilias Diakonikolas, Daniel M. Kane, Degree-d Chow Parameters Robustly Determine Degree-d PTFs (and Algorithmic Applications) Symposium on Theory Of Computation (STOC) 2019.
- Daniel M Kane, Sankeerth Rao A PRG for Boolean PTF of Degree 2 with Seed Length Subpolynomial in ε and Logarithmic in n, Conference on Computational Complexity (CCC) 2018.
- Valentine Kabanets, Daniel M. Kane, Zhenjian Lu A Polynomial
Restriction Lemma with Applications, Symposium
on Theory Of Computation (STOC) 2017.
- Parikshit Gopalan, Daniel M. Kane, Raghu Meka, Pseudorandomness via the
Discrete Fourier Transform, Foundations
of Computer Science (FOCS) 2015, SIAM Journal of computing (SICOMP) Vol 47, no 6 pp. 2451-2487.
- Daniel M. Kane A Polylogarthmic PRG for
Degree 2 Threshold Functions in the Gaussian Setting, Conference on Computational Complexity (CCC) 2015.
- Daniel M. Kane The Average Sensitivity
of an Intersection of Half Spaces, Symposium
on the Theory Of Computing 2014, journal
version (open access) in Research In
the Mathematical Sciences Vol. 1 no 1 (2014).
- Daniel M. Kane A Pseudorandom Generator
for Polynomial Threshold Functions of Gaussians with Subpolynomial Seed Length,
Conference on Computational Complexity
2014.
- Daniel M. Kane, Adam Klivans, Raghu Meka Learning Half Spaces Under
Log-Concave Densities: Polynomial Approximation and Moment Matching, Conference on Learning Theory (COLT) 2013.
- Daniel M. Kane The Correct Exponent for
the Gotsman-Linial Conjecture, Conference
on Computational Complexity (CCC) 2013 (won best paper award).
- Daniel
M. Kane, Raghu Meka A PRG
for Lipschitz Functions of Polynomials with Applications to Sparsest Cut, Symposium on the Theory of Computation (STOC) 2013.
- Daniel M. Kane A Structure
Theorem for Poorly Anticoncentrated Gaussian Chaoses and Applications to the
Study of Polynomial Threshold Functions, Foundations of Computer Science (FOCS) 2012, pp. 91-100; journal
version Annals of Probability, Vol. 45 no. 3 (2017) pp. 1612-1679.
- Daniel M. Kane, A
Small PRG for Polynomial Threshold Functions of Gaussians, Foundations of Computer Science (FOCS)
2011.
- Daniel M. Kane k-Independent Gaussians
Fool Polynomial Threshold Functions, Conference
on Computational Complexity (CCC), 2011.
- Ilias Diakonikolas, Daniel M. Kane, Jelani
Nelson, Bounded
Independence Fools Degree-2 Threshold Functions, Foundations of Computer Science (FOCS) 2010.
- Daniel M. Kane The
Gaussian Surface Area and Noise Sensitivity of Degree-d Polynomial Threshold
Functions, in Conference on
Computational Complexity (CCC) 2010, pp. 205-210 (Won CCC 2010 best student
paper).
- Streaming Algorithms:
- Daniel M. Kane, Kurt Mehlhorn, Thomas Sauerwald,
He Sun Counting
Arbitrary Subgraphs in Data Streams, International
Colloquium on Automata, Languages and Programming (ICALP) 2012, pp. 598-609.
- Daniel M. Kane, Jelani Nelson, Ely Porat,
David P. Woodruff, Fast
Moment Estimation in Data Streams in Optimal Space, Symposium on the
Theory of Computing (STOC) 2011.
- Daniel M. Kane, Jelani Nelson, David P. Woodruff
An Optimal Algorithm
for the Distinct Elements Problem, Symposium
on Principles of Database Systems (PODS) 2010 (Won PODS 2010 best paper,
and 2010 IBM research Pat Goldberg Memorial Best Paper Award in Computer
Science, Electrical Engineering and Math). Invited
to Journal of the ACM.
- Daniel M. Kane, Jelani Nelson, David P. Woodruff
On the Exact Space
Complexity of Sketching and Streaming Small Norms, Proceedings of the 21st Annual ACM-SIAM Symposium on Discrete
Algorithms (SODA) 2010.
- Johnson-Lindenstrauss:
- Daniel M. Kane, Jelani Nelson, Sparser
Johnson-Lindenstrauss Transforms, Symposium
on Discrete Algorithms (SODA) 2012, Journal of the ACM, Vol. 61 no. 1,
Article 4, 2014.
- Daniel M. Kane, Raghu Meka, Jelani Nelson, Almost Optimal
Explicit Johnson-Lindenstrauss Transforms, International Workshop on Randomization and Computation (RANDOM), 2011.
- Daniel Kane, Jelani Nelson, A Derandomized Sparse
Johnson-Lindenstrauss Transform, superseded by Sparser
Johnson-Lindenstrauss Transforms (above).
- Circuit Complexity:
- Security:
- Computational Geometry:
- Daniel M. Kane, Gregory N. Price, Erik D.
Demaine, A
Pseudopolynomial Algorithm for Alexandrov's Theorem, Algorithms and Data Structures Symposium (WADS) 2009. Also in Lecture
Notes in Computer Science, 5664 (2009) pp. 435–446.
- Timothy G. Abbott, Michael A. Burr, Timothy M.
Chan, Erik D. Demaine, Martin L. Demaine, John Hugg, Daniel Kane, Stefan
Langerman, Jelani Nelson, Eynat Rafalin, Kathryn Seyboth, Vincent Yeung, Dynamic
Ham-Sandwich Cuts in the Plane, Computational
Geometry: Theory and Applications, Vol. 42, no. 5, July 2009, pages
419–428. Special issue of selected papers
from the 17th Canadian Conference on Computational Geometry, 2005.
- Tim Abbott, Erik D. Demaine, Martin L. Demaine,
Daniel M. Kane, Setfan Langerman, Jelani Nelson, Vincent Yeung Dynamic Ham-Sandwich
Cuts of Polygons in the Plane Canadian
Conference on Computational Geometry, (2005) pp. 61-64.
- Other Computer Science:
- Daniel M. Kane, Ilias Diakonikolas A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points, Conference on
Learning Theory (COLT) 2023.
- Daniel Beaglehole, Max Hopkins, Daniel Kane, Sihan Liu, Shachar Lovett Sampling Equilibria: Fast No-Regret Learning in Structured Games, Symposium on Discrete
Algorithms (SODA) 2023.
- Alaa Maalouf, Murad Tukan, Eric Price, Daniel Kane, Dan Feldman Coresets for Data Discretization and Sine Wave Fitting, Conference on Artificial Intelligence and Statistics (AISTATS) 2022.
- Daniel Kane, Andreas Fackler, Adam Gągol, Damian Straszak, Highway: Efficient Consensus with Flexible Finality, in preparation.
- Daniel M. Kane, Shahed Sharif, Alice Silverberg Quantum Money from Quaternion Algebras, MathCrypt 2022.
- Venkata Gandikota, Daniel Kane, Raj Kumar Maity, Arya Mazumdar Vector Quantized Stochastic Gradient Descent, 4th Asilomar Conference on Signals, Systems and Computers (Asilomar) 2020, journal version in IEEE Transactions on Information Theory, 2022.
- Jeffery S. Cohen, Daniel M. Kane Bounds on the
Independence Required for Cuckoo Hashing, manuscript.
- Chung-Kuan Cheng, Daniel
M. Kane, Ilgweon Kang, Fang Qiao, 3D Floorplan
Representations: Corner Links and Partial Ordering, IEEE International 3D Systems Integration
Conference (3DIC) 2016, Journal Version: Kang, I., Qiao, F., Park, D., Kane, D., Young, E.F.Y., Cheng, C.K., Graham, R. Three-dimensional Floorplan Representations by Using Corner Links and Partial Order ACM Transactions on Design Automation of Electronic Systems (TODAES), 24(1), p.13, 2018.
- Daniel M Kane, Shachar Lovett, Sankeerth Rao, The Independence Number
of the Birkhoff Polytope Graph and Applications to Maximally Recoverable Codes,
Foundations Of Computer Science
(FOCS) 2017, journal version SIAM Journal of computing (SICOMP) Vol 48, no 4 (2019) pp 1425-1435.
- Daniel M. Kane, Osamu Watanabe A Short Implicant of CNFs with
a Relatively Many Satisfying Assignments, International Symposium on Algorithms And Computation (ISAAC) 2014;
journal version Algorithmica, (2016),
DOI: 10.1007/s00453-016-0125-z.
- Daniel M. Kane A Low-Depth
Monotone Function Given by a Low-Depth Decision Tree
that is not an Approximate Junta, Theory
of Computing Vol. 9 (2013) pp. 587-592.
- Eric Blais, Daniel Kane Tight Bounds
for Testing k-Linearity, International
Workshop on Randomization and Computation (RANDOM) 2012.
- Daniel M. Kane, Samuel A. Kutin, Quantum
Interpolation of Polynomials, presented at Combinatorics, Groups, Algorithms, and Complexity (conference in honor
of Laci Babai’s 60th birthday (CGAC) 2010, journal version in Quantum Information and Computation Vol.
11 no. 1&2 (2011).
- Daniel M. Kane Unary Subset-Sum is in
Logspace, unpublished.
- Erik D. Demaine, Dion Harmon, John Iacono,
Daniel M. Kane, Mihai Pǎtraşcu, The Geometry of Binary
Search Trees, in Symposium on
Discrete Algorithms (SODA) 2009.
- Daniel M. Kane, Jonathan M. Kane Dropping Lowest Grades
Mathematics Magazine, Vol. 79 (June 2006) pp. 181-189.
- Tim G. Abbott, Daniel M. Kane, Paul Valiant On the
Complexity of Two-Player Win-Lose Games Foundations Of Computer Science (FOCS) 2005 (Won
Machtey award for best student paper).
- Mathematics:
- Number Theory:
- Arithmetic Statistics:
- Daniel M. Kane, Zev Klagsbrun, On the Joint Distribution
Of Selφ(E/Q) and Selφ^(E/Q) in
Quadratic Twist Families, in preparation.
- Daniel M. Kane, Jack A. Thorne, On
the φ-Selmer Groups of Elliptic Curves y2 = x3 – Dx, Mathematical
Proceedings of the Cambridge Philosophical Society, Vol 163 no 1 (2017) pp. 1–23.
- Manjul Bhargava, Daniel M. Kane, Hendrik W.
Lenstra Jr., Bjorn Poonen, Eric Rains Modeling the Distribution of
Ranks, Selmer Groups, and Shafarevich-Tate Groups of Elliptic Curves, Cambridge Journal of Mathematics, Vol. 3
(2015), pp. 275-321.
- Daniel M. Kane On
the Ranks of the 2-Selmer Groups of Twists of a Given Elliptic Curve, Algebra & Number Theory, 7 issue 5 (2013),
pp. 1253-1297.
- Additive Combinatorics:
- Other Number Theory:
- Daniel M. Kane, Robert C. Rhoades A Proof of Andrews' Conjecture
on Partitions with no Short Sequences, Forum of Mathematics
Sigma, Vol 7, 2019.
- Daniel M. Kane On the Crossing
Number of Complete Graphs with an Uncrossed Hamiltonian Cycle, manuscript.
- Daniel M. Kane On the
Number of ABC Solutions with Restricted Radical Sizes, Journal of Number
Theory, (2015), pp. 32-43.
- Andrew Granville, Daniel M Kane, Dimitris Koukoulopoulos, Robert J Lemke Oliver Best Possible Densities of Dickson m-Tuples, as a Consequence of Zhang–Maynard–Tao in Analytic Number Theory Springer, 2015.
- Daniel M. Kane, Scott Duke Kominers Asymptotic Improvements of
Lower Bounds for the Least Common Multiples of Arithmetic Progressions, Canadian Mathematical Bulletin, Vol. 57
(2014), pp. 551-561
- Noam D. Elkies, Daniel M. Kane, Scott Duke
Kominers, Minimal
S-Criteria May Vary in Size, Journal de Theorie des Nombres de Bordeaux, Vol. 23 no. 3 (2013) pp. 557-563.
- Daniel M. Kane An Asymptotic for the
Number of Solutions to Linear Equations in Prime Numbers from Specified Chebotarev
Classes, International Journal of Number Theory, Vol. 9 no. 4 (2013) pp. 1073-1111.
- Bakir Farhi, Daniel Kane New Results on the Least Common
Multiple of Consecutive Integers, Proceedings
of the AMS, 137 (2009), no. 6, pp. 1933-1939.
- Daniel Kane, Steven Sivek On the Sn-Modules
Generated by Partitions of a Given Shape, The Electronic Journal of Combinatorics, 15 (2008), 12 pages.
- Daniel M. Kane On
Lower Bounds on the Size of Sums-of-Squares Formulas Journal of Number
Theory, 128 (2008) pp. 639-644.
- Daniel M. Kane Improved Bounds on the
Number of Ways of Expressing t as a
Binomial Coefficient, Integers:
Electronic Journal of Combinatorial Number Theory, Vol. 7 (2007), #A53 pp.
1-7.
- Daniel M. Kane Asymptotics of McKay
Numbers for Sn, Journal of Number Theory, Vol. 124 (2007) pp.
200-228.
- Daniel M. Kane Generalized
Base Representations Journal of Number Theory, Vol. 120 (2006) pp. 92-100.
- Daniel M. Kane An
Elementary Derivation of the Asymptotics of Partition Functions The
Ramanujan Journal, Vol. 11 no. 1(2006) pp. 49-66.
- Daniel M. Kane On the Number of Ways of
Writing t as a Product of Factorials Integers: Electronic Journal of
Combinatorial Number Theory, Vol. 5 (2005), #A02, pp. 1-10.
- Daniel M. Kane Resolution of a
Conjecture Involving Cranks of Partitions of Andrews and Lewis Proceedings
of the American Mathematical Society, Vol. 132 No. 8(2004), pp. 2247-2256.
-
Daniel M. Kane New Bounds on the
Number of Representations of t as a Binomial Coefficient Integers: Electronic Journal of
Combinatorial Number Theory, Vol. 4 (2004), #A07, pp. 1-10.
- Semitoric Manifolds:
- COMAP MCM Papers:
- Dan Gulotta, Daniel M. Kane, Andrew Spann Electoral Redistricting with
Moment of Inertia and Diminishing Halves Models(3.81 MB) UMAP Journal, Vol. 28 (2007), pp.
281-299.
- Dan Gulotta, Daniel M. Kane, Andrew Spann Application of Min-Cost Flow
to Airline Accessibility Services UMAP Journal, Vol. 27 (2006), pp.
367-385.
- Dan Gulotta, Daniel M. Kane, Andrew Spann Lane Changes and Close
Following: Troublesome Tollbooth Traffic(6 MB) UMAP
Journal, Vol. 26 no. 3 (2005) pp. 251-264.
- Other Mathematics
- Daniel M. Kane, Scott Duke Kominers Prisoners, Rooms, and Lightswitches, Electronic Journal of Combinatorics, Vol 28 (1), 2021 pp. 1-27.
- Daniel M. Kane Small Designs for Path
Connected Spaces and Path Connected Homogeneous Spaces, Transactions of the AMS, Vol. 367
(2015), pp. 6387-6414.
- Daniel M. Kane Canonical Projective
Embeddings of the Deligne-Lusztig Curves Associated to 2A2,
2B2 and 2G2, International Mathematics Research Notices,
(2015) pp. 1158-1189.
- Bobbie Chern, Persi Diaconis, Daniel M. Kane,
Robert C. Rhoades Central Limit
Theorems for Some Set Partition Statistics, Advances in Applied Mathematics, Vol. 70 (2015), pp. 92–105.
- Bobbie Chern, Persi Diaconis, Daniel M. Kane,
Robert C. Rhoades Closed
Expressions for Averages of Set Partition Statistics, Research in the Mathematical Sciences, Vol. 1 (2014) no. 2.
- Chris Dodd, Phakawa Jeasakul, Anne
Jirapattanakul, Daniel M. Kane, Becky Robinson, Noah Stein, Cesar E. Silva Ergodic Properties of a Class
of Discrete Abelian Group Extensions of Rank-One Transformations, Colloquium Mathematicum, 119 (2010), pp.
1-22.
- Daniel M. Kane On Solving Games
Constructed Using Both Shortened and Continued Conjunctive Sums, Integers: Electronic Journal of
Combinatorial Number Theory, 10 (2010), pp. 849-878.
- Daniel M. Kane A
Partition of the Positive Reals into Algebraically Closed Subsets,
unpublished.
- Daniel M. Kane Weak Mixing of a
Transformation Similar to Pascal, Colloquium Mathematicum,
Vol. 108 no. 1(2007), pp. 135-140.
Coauthors: Tim Abbott, Daniel Beaglehole, Mihir Bellare, Manjul Bhargava,
Eric Blais, Olivier Bousquet, Michael A. Burr, Clement Canonne, Timothy M. Chan, Xue Chen, Chung-Kuan Cheng, Yu Cheng, Yuqian Cheng, Bobbie Chern,
Jeffery Cohen, Yuval Dagan, Erik Demaine,
Martin Demaine, Ilias Diakonikolas, Chris Dodd, Noam Elkies, Andreas Fackler, Bakir Farhi, Dan Feldman, Yuval Filmus, Adam Gągol, Venkata Gandikota, Rong Ge, Surbhi Goel, Themis Gouleakis, Ron Graham,
Andrew Granville, Parikshit Gopalan, Ben Green,
Dan Gulotta, Shivam Gupta, Max Hopkins, Samuel B. Hopkins, John Hugg, John Iacono, Russell Impagliazzo, Joseph Jaeger, Phakawa Jeasakul,
He Jia, Anne Jirapattanakul, Gautam Kamath, Ilgweon Kang, Valentine Kabanets, Jonathan Kane, Ilgweon Kang, Sushrut Karmalkar, Zev Klagsbrun, Adam Klivans, Scott Kominers, Daniel Kongsgaard, Vasileios Kontonis, Pravesh Kothari, Dimitris Koukoulopoulos, Samuel A. Kutin, Setfan Langerman, Rex Lei, Robert Lemke Oliver, Hendrik W.
Lenstra Jr., Jerry Li, Sihan Liu, Roi Livni, Shachar Lovett, Zhenjian Lu, Yuetian Luo, Alaa Maalouf, Gaurav Mahajan, Pasin Manurangsi, Raj Kumar Maity, Arya Mazumdar, Kurt Mehlhorn, Raghu Meka, Ankur Moitra, Shay Moran, Michal Moshkovitz, Jelani Nelson, Vladimir Nikishkin, Ryan O'Donnell, Joseph Palmer, Dongwon Park, Mihai
Pǎtraşcu, John Peebles, Alvaro Pelayo, Ankit Pensia, Thanasis Pittas, Bjorn Poonen, Ely Porat, Eric Price, Gregory N. Price, Fang Qiao, Eynat
Rafalin, Eric Rains,
Sankeerth Rao, Lisheng Ren, Robert Rhoades, Becky Robinson, Phillip Rogaway, Carlo Sanna, Thomas Sauerwald, Rocco A. Servedio, Kathryn Seyboth, Jeffrey Shallit, Shahed Sharif, Cesar E. Silva, Alice Silverberg, Mahdi Soltanolkotabi, Zhao
Song, Jessica Sorrell, Andrew
Spann, Jacob Steinhardt, Alistair Stewart, Noah Stein, Damian Straszak, He Sun, Yuxin Sun, Csaba Szepesvári, Li-Yang Tan, Terence Tao, Kevin Tian, Jack A. Thorne, Murad Tukan, Christos Tzamos, Paul Valiant, Santosh Vempala, Puqian Wang, Osamu Watanabe, Gellért Weisz, Ryan Williams, David Woodruff,
Vincent Yeung, Amir Yehudayoff, Evangeline Fung Yu Young, Nikos Zarifis, Anru Zhang, Zhicheng Zheng