Daniel M. Kane
CV
(Last updated 9/25/2023)
Work Address: Department of Computer Science
and Engineering, 9500 Gilman Drive #0404, La Jolla, CA 92093-0404
Email:
dakane at ucsd dot edu
Phone: (858) 246-0102
Website: http://cseweb.ucsd.edu/~dakane/
Citizenship: USA
Education:
- Harvard University:
September 2007-May 2011
- M.A. in Mathematics,
June 2008
- Ph.D. in Mathematics,
May 2011
- Research Advisors:
Barry Mazur, Benedict Gross, Henry Cohn
- Massachusetts Institute
of Technology: September 2003- May 2007
- B.S. in Mathematics
with Computer Science, June 2007
- B.S. in Physics, June
2007
- Graduated Phi Beta
Kappa with a Perfect GPA
- Research Advisors:
Erik Demaine, Joe Gallian,
Cesar Silva
- University of
Wisconsin-Madison: September 1999 – May 2003, enrolled as a special
student while in high school
- 20 Courses in
Mathematics, Physics, Computer Science and Economics
- GPA 3.99/4.00
- Research Advisor: Ken
Ono
Employment:
Full Professor Mathematics and Computer Science and Engineering, University of California, San Diego, 2023-present.
Associate Professor Mathematics and
Computer Science and Engineering, University of California, San Diego,
2019-2023.
Assistant Professor Mathematics and
Computer Science and Engineering, University of California, San Diego,
2014-2019.
Postdoctoral Fellow, Stanford University Department of Mathematics
(2011-2014) [on NSF fellowship]
Other Employment/Summer Internships:
- Consulting for CASPER Labs 2019-present.
- Consulting for AIble (2018-2019).
- Intern at Center for
Communications Research (summers of 2007, 2008, 2009, 2011, 2012, 2013,2014, sporadic consulting 2007-2020).
- Consultant for Beyondcore (2011-2014).
- Intern at Microsoft Research
New England working with Henry Cohn (summer 2010).
- Consultant for Professor
Peter Coles of the Harvard Business School (2008-2009).
- MIT Undergraduate Research
Opportunities Program (UROP) working under Erik Demaine on problems in
theoretical computer science (summer 2006).
- Participant in the Duluth Research
Experiences for Undergraduates program (summer 2005, as a visitor in
2003 and 2006).
- Participant in the SMALL Research Experiences for
Undergraduates program at Williams College working under Cesar Silva
(summer 2004).
Research
Interests:
My research interests are broad and cover a number of areas
in mathematics and computer science, but most of what I do is in number theory,
combinatorics, or complexity theory. For the last couple years, the bulk of my
work has been on computational statistics / machine learning.
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.
Talks:
- Daniel M. Kane A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning Symposium on the Theory Of Computation (STOC), June 2023.
- Daniel M. Kane Algorithmic High-Dimensional Robust Statistics [Video Recording] University of Sydney Basser Seminar Series, April 2023.
- Daniel M. Kane Ak Testing of Distributions FODSI Workshop on Sublinear Algorithms, August 2022, USC Prob/Stat Seminar 2022, UW-Madison Theory Seminar November 2022.
- Daniel M. Kane Non-Gaussian Component Analysis via Lattice Basis Reduction COLT June 2022.
- Daniel M. Kane The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals Talk for UCSD theory seminar, May 2022.
- Daniel M. Kane SQ Lower Bounds for Learning Halfspaces with Massart Noise Talk for Simons Institute Workshop on Rigorous Evidence for Information-Computation Trade-offs, September 2021.
- Daniel M. Kane Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models Talk for the SoS+TCS Reading group, March 2021.
- Daniel M. Kane Point Location and Active Learning: Learning Halfspaces Almost Optimally
One World Mathematics of INformation, Data, and Signals (1W-MINDS)
Seminar January 2021, University of Texas at Austin Theory Seminar,
March 2021.
- Daniel M. Kane Robust Learning of Mixtures of Gaussians SODA January 2021.
- Daniel M. Kane Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models FOCS October 2020, Simons Institute workshop on learning and testing in high dimensions, December 2020.
- Daniel M. Kane STOC 2019 Tutorial on Recent Advances in High-Dimensional Robust Statistics Learning Gaussian Covariance Robustly, Robust Sparse Statistics, Robust List Decoding and Utilizing High Degree Moments, June 2019.
- Daniel M. Kane Robust List Decoding of Spherical Gaussians Simons Institute Robust and High Dimensional Statistics Workshop, October 2018.
- Daniel M. Kane Quantum Money From Modular Forms Open questions in number theory and cryptography conference, September 2018.
- Daniel M. Kane List Decoding via Filters, TTIC Robust Statistics Workshop, August 2018.
- Daniel M. Kane Statistical Query Lower Bounds for Robust Statistics Problems, TTIC Robust Statistics Workshop, August 2018.
- Daniel M. Kane Learning Gaussian Covariance Robustly, TTIC Robust Statistics Workshop, August 2018.
- Daniel M. Kane Sample Complexity and Good Sets, TTIC Robust Statistics Workshop, August 2018.
- Daniel M. Kane Fooling Fourier Shapes, Oxford Complexity Theory Workshop, July 2018.
- Daniel M. Kane List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians, Symposium on the Theory Of Computation (STOC), June 2018.
- Invited to give a talk at Open questions in number theory and cryptography conference in celebration of Alice Silverberg's 60th birthday.
- Invited to give a talk at HALG 2018
- Daniel M. Kane Recent Advances in High Dimensional Robust Statistics Institute for Advanced Study, December 2017.
- Daniel M. Kane Recent Results on The Queen
Packing Problem UC Berkeley Combinatorics seminar, February 2017.
-
Daniel M. Kane A
New Approach to Distribution Testing, UCSD CS Theory Seminar, October 2015;
Harvard CS Theory Seminar, August 2016; Banff Center Complexity Theory
Workshop, September 2016.
-
Daniel M. Kane Average Phi-Selmer of Elliptic
Curves, Arithmetic Statistics and Cohen Lenstra Heuristics Workshop at
Warwick, June 2016.
-
Daniel M. Kane A Polylogarithmic PRG
for Degree-2 PTFs in the Gaussian Setting, Conference on Computational
Complexity, June 2015.
-
Daniel M. Kane Connection Regions on a
Randomly Colored Board given at the awards ceremony for the UCSD honors
math contest, May 2015.
-
Daniel M. Kane On a Problem Related to the
ABC Conjecture given at Southern California Number Theory Day, October
2014.
-
Daniel M. Kane The Average
Sensitivity of an Intersection of Halfspaces, Symposium on the Theory of
Computation, June 2014.
- Daniel M. Kane On a Problem Related to the
ABC Conjecture given at CMU March 2014.
- Daniel M. Kane An Optimal
Algorithm for the Distinct Elements Problem (joint work with Jelani Nelson
and David Woodruff) given at UCSD February 2014; UW-Madison March 2014.
-
Daniel M. Kane A Pseudorandom
Generator for Polynomial Threshold Functions with Subpolynomial Seed Length
MIT Algorithms and Complexity Seminar, November 2013; UCSD CS Theory Seminar,
October 2014; short
version given at Conference on Computational Complexity, June 2014.
-
Daniel M. Kane Dropping Lowest Grades
Stanford math undergraduate colloquium, October 2013; UCSD Math 196 (undergrad
colloquium) talk, October 2014.
-
Daniel M. Kane, Raghu Meka, A PRG for Lipchitz
Functions of Polynomials with Applications to Sparest Cut, Symposium on the
Theory Of Computation, June 2013.
-
Daniel M. Kane The Correct Exponent for
the Gotsman-Linial Conjecture, Conference on Computational Complexity, June
2013; Longer, informal talk at the Microsoft Research/MIT Theory Reading Group,
May 2013; Stanford theory lunch, June 2014.
-
Daniel M. Kane Bounds on the
Independence Required for Cuckoo Hashing (joint work with Jeffery Cohen)
CMU Seminar on Algorithms, Combinatorics, and Optimization, April 2013.
-
Daniel M. Kane The Asymptotics of
Partitions without k-Sequences (joint work with Robert Rhoades) American Mathematical
Society Special Session on The Influence of Ramanujan on
His 125th Birthday, Joint Mathematics Meetings, San Diego, CA, January 2013. Longer version,
given at Bay Area Discrete Math Day (BAD Math Day), April 2013.
- Daniel M. Kane Diffuse Decompositions of
Polynomials, Symposium on the Analysis of Boolean Functions: New Directions
and Applications, St. John Virgin Islands, February 2012; MIT Probability
Seminar, Cambridge MA, March 2012; San Jose State University Mathematics
Colloquium, San Jose CA, November 2012; short version at Symposium on the
Foundations of Computer Science (FOCS), New Brunswick NJ, October 2012; Stanford
University Probability Seminar, Stanford, CA, December 2012; IAS Computer
Science/Discrete Math Seminar April, 2013; Columbia CS Theory Seminar, April
2013; University of Wisconsin-Madison Number Theory-Representation Theory
Seminar November 2013; Courant Institute December 2013; UCSD January 2014; CMU
March 2014; University of Edinburgh, November 2014; UCLA Analysis and PDE
Seminar January 2017.
-
Daniel M. Kane The Number of Ways of
Expressing a Number as a Binomial Coefficient, Stanford University
Mathematical Organization talk, Stanford CA, October 2011.
-
Daniel M. Kane A Small PRG for Polynomial
Threshold Functions of Gaussians, Symposium on the Foundations Of Computer
Science (FOCS), Palm Springs CA, October 2011.
-
Daniel M. Kane Noise
Sensitivity of Polynomial Threshold Functions, MSRI Workshop on
Quantitative Geometry, Berkeley
CA, August 2011.
- Daniel M. Kane k-Independence Fools
Polynomial Threshold Functions of Gaussians, Conference on
Computational Complexity (CCC), San Jose CA, June 2011.
-
Daniel M. Kane Ranks of 2-Selmer of Twists
of an Elliptic Curve, South Eastern Regional Meeting on Numbers
(SERMON), Savannah GA, April 2011; Workshop on Arithmetic of Abelian
Varieties in Families at Centre Interfacultaire Bernoulli (CIB), Lausanne
Switzerland, November 2012; UCLA Number Theory Seminar, December 2013; Stanford
Number Theory Seminar, January 2014; Longer version
given at the Quebec-Vermont Number Theory Seminar, Montreal, January 2014.
-
Daniel M. Kane The
FT-Mollification Method, Workshop on Analysis and Geometry of Polynomial
Threshold Functions, Princeton
NJ, October 2010.
- Daniel M. Kane The ABC Conjecture
Microsoft Research, Cambridge,
MA, July 2010.
-
Daniel Kane The Gaussian Surface Area
and Noise Sensitivity of Degree-d Polynomial Threshold Functions,
Conference on Computational Complexity (CCC), Cambridge MA, June 2010; China Theory
Week, Beijing China, September 2010.
-
Dan Gulotta, Daniel Kane, and Andrew Spann, Electoral
Redistricting with Moment of Inertia and Diminishing Halves Models
SIAM meeting, San Diego CA, July 2008.
-
Daniel M. Kane The Number of Ways of
Expressing t as a Binomial Coefficient Joint Mathematics Meetings,
January 2007.
-
Daniel M. Kane On
Solving Games Constructed Using Both Shortened and Continued Conjunctive Sums Joint
Mathematics Meetings, New
Orleans LA,
January 2006.
-
Daniel M. Kane Ergodic Properties of
Group Extensions of Rank 1 Transformations Part II Mathfest, Providence RI,
August 2004.
Books:
- Ilias Diakonikolas and Daniel M. Kane Algorithmic High-Dimensional Robust Statistics, Cambridge University Press, 2023.
- Kiran S. Kedlaya, Daniel M. Kane, Jonathan Kane, Evan M. O'Dorney, The William Lowell Putnam Mathematical Competition 2001-2016: Problems, Solutions, and Commentary, AMS/MAA, 2020.
Other Books contributed to:
- Jonathan Kane, Writing Proofs in Analysis, Springer, 2016.
- Andreescu,
T., Feng, Z, and Loh, P.-S., USA & International
Mathematical Olympiads 2003, MAA,
2004.
- Andreescu, T., Feng, Z, and Loh, P.-R., Mathematical Olympiads
2001-2002: Problems and Solutions from Around the World, MAA,
2004.
- Andreescu, T., Feng, Z, and Lee, G., Jr.,
Mathematical Olympiads
2000-2001: Problems and Solutions from Around the World, MAA, 2003.
- Andreescu, T., and Feng, Z, Mathematical Olympiads
1999-2000: Problems and Solutions from Around the World, MAA, 2001.
- Andreescu, T., and Feng, Z, Mathematical Olympiads
1998-1999: Problems and Solutions from Around the World, MAA, 2000.
Grants/Fellowships:
- Computational Statistics and Blockchain Research - grant from Casper Labs
- NSF Medium Grant (with Ilias Diakonikolas) [Award ID 2107547] (2021-2025)
- Sloan Fellowship (2017-2019)
- NSF Career Grant [Award ID
1553288] (2016-2021)
- NSF Postdoctoral Fellowship
[Award number 1103688] (2011-2014)
Awards and Honors:
- Conference on Computational
Complexity Best paper award, 2013.
- IBM research Pat Goldberg
Memorial Best Paper Award in Computer Science, Electrical Engineering and
Math, 2010.
- Symposium on Principles of
Database Systems Best Paper Award 2010.
- Conference on Computational
Complexity Best Student Paper, 2010.
- Jon A. Bucsela
prize for top senior in MIT's mathematics department, 2007.
- AMS/MAA/SIAM Frank and Brennie Morgan Prize for research by an undergraduate,
2007.
- Machtey Award for Best
Student Paper at IEEE Symposium on Foundations of Computer Science, 2005.
- Member of 3 person COMAP
Mathematical Contest in Modeling Team 2004, 2005, 2006, 2007. Achieved an
"Outstanding" in 2005, 2006, 2007. Won the Ben Fusaro Award for
most creative solution in 2004. Won the INFORMS Award in 2006. Won the
SIAM Award in 2007.
- Putnam Fellow (among top 5)
2003, 2004, 2005, 2006 and a Member of MIT's 1st place Team in 2003, 2004
in the William Lowell Putnam Mathematical Competition.
- Gold Medalist at
International Mathematical Olympiad as Member of USA Team, 2003, 2002.
Teaching:
Formal Instruction:
- Ran Theory CSE Seminar at UCSD (Spring 2020)
- Instructor for Math 154 (Graph Theory) at UCSD (Spring 2020, Fall 2021)
- Instructor for Math 204C (Analytic Number Theory) at UCSD (Spring 2019)
- Instructor for Math 11 (Probability and Statistics) at UCSD (Winter 2018, Winter 2019)
- Instructor for CSE 203A
(Randomized Algorithms) at UCSD (Fall 2017)
- Instructor for CSE 291
(Statistical Learning Theory) at UCSD (Spring 2017, Winter 2020)
- Instructor for Math 96
(Putnam Seminar) at UCSD (Fall 2016, Fall 2017, Fall 2018, Fall 2019, Fall 2021, Fall 2022)
- Instructor for Math 205
(Topics in Number Theory: Elliptic Curves) at UCSD (Winter 2016)
- Instructor for Math 184A/184
(Combinatorics) at UCSD (Fall 2015, Fall 2016, Spring 2018, Spring 2021, Spring 2022, Fall 2022)
- Instructor for CSE 291
(Analysis of Polynomial Threshold Functions) at UCSD (Spring 2015)
- Instructor for CSE
101
(Introduction to Algorithms) at UCSD (Winter 2015, Spring 2016,
Spring 2017, Spring 2018, Fall 2018, Fall 2019, Winter 2021, Winter 2022, Winter 2023)
- Instructor for Math 110
(Applied Number Theory and Field Theory) at Stanford (Spring 2014)
- Instructor for Math 113
(Linear Algebra and Matrix Theory) at Stanford (Fall 2013)
- Lecturer for two sections of
Math 51 (Linear Algebra and Differential Multivariable Calculus) at
Stanford (Winter 2013)
- Teaching Fellow (lecturer)
for Math 21b (Linear Algebra/ Differential Equations) at Harvard (Fall
2009)
- Teaching Fellow for Math Xa (Precalc/Calc I) at Harvard (Fall 2008)
- TA (discussion section
leader) for 18.03 (Differential Equations) at MIT (Spring 2007)
- TA for 18.022 (Honors Calc
II) at MIT (Fall 2006)
Online Courses:
Mentorship:
- Grad Students: Max
Hopkins (joint adviser with Shachar Lovett) 2018-present, Sihan Liu
2021-present, Anthony Ostuni (joint adviser with Shachar Lovett)
2021-present.
- Mentoring a local high
school student on a mathematical research project (2011-2013)
- Instructor at the Math
Olympiad Summer Program (June 2011)
- Helped Teach the Harvard
Mathematics Department’s Quals
Tutorials, (Spring 2008, Fall 2008, Spring 2009, Fall 2009, Spring 2010)
Service:
- On Editorial Board of SICOMP (2020-2022).
- On PC for ITCS 2022.
- Helped grade the Putnam exam, 2020.
- Program Committee for FOCS 2019.
- Co-organized STOC 2019 Tutorial on Recent Advances in High-Dimensional Robust Statistics.
- On organizing committee for the UCSD Honors Mathematics Contest 2015-present. Chair of committee 2018-present.
- Program Committee for COLT 2019
- Co-organized workshop in Computational Efficiency & High Dimensional Robust Statistics, sponsored by TTI-Chicago, August 2018.
- Program Committee for RANDOM 2018.
- On NSF panel in 2016, 2018, 2020.
- Program Committee for
Symposium On Discrete Algorithms (SODA) 2016, 2018, 2022.
- USA Mathematical Olympiad
grader, 2010,2011.
- Helped proctor/grade the
Harvard-MIT Mathematics Tournament, 2004-2008
- Ad Hoc reviewer for:
- Journals: Integers: the Electronic Journal of Combinatorial Number Theory;
Proceedings of the American Mathematical Society; Comptes Rendus
Mathematique;
Bulletin of the London Mathematical Society; SIAM Journal on Computing;
ACM Transactions on Algorithms; Algebra and Number Theory; Annals of
Combinatorics; Archiv
der Mathematik; Journal Applicable Analysis and
Discrete Mathematics; Journal of Combinatorial Optimization; Chicago
Journal of Theoretical Computer Science; Israel Journal of Mathematics;
Forum Mathematicum; Comptes Rendus
a Académie des Sciences; Journal of Machine Learning Research
- Conferences: Symposium on Theory Of Computing (STOC); Computational Complexity
(CCC); Symposium on Discrete Algorithms (SODA); ACM Symposium on
Principles of Database Systems(PODS); Innovations in Theoretical Computer
Science (ITCS)
- Grant
Evaluation: Assisted in evaluation of a grant for
the Army Research Office
Society Memberships:
- Association for Computing
Machinery