Daniel M. Kane
CV
(Last updated 12/16/2024)
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:
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:
- Ilias Diakonikolas, Daniel M. Kane Implicit High-Order Moment Tensor Estimation and Learning Latent Variable Models, in preparation.
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis,
Christos Tzamos, Nikos Zarifis Agnostically Learning
Multi-index Models with Queries, 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.
- Ery Arias-Castro, Clement Berenfeld, Daniel Kane Theoretical
Foundations of Ordinal Multidimensional Scaling, Including
Internal and External Unfolding, in preparation.
- Scott Arens, Daniel M. Kane Partial Taking Valuations: Part I International Right of Way Association, to appear.
- Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee,
Thanasis Pittas Clustering
Mixtures of Bounded Covariance Distributions Under Optimal
Separation, Symposium on Discrete
Algorithms (SODA) 2025.
- Ilias Diakonikolas, Daniel Kane, Mingchen Ma Active
Learning of General Halfspaces: Label Queries vs Membership
Queries, Advances in Neural Information Processing
Systems (NeurIPS) 2024.
- Max Hopkins, Russell Impagliazzo, Daniel Kane, Sihan Liu,
Christopher Ye Replicability
in High Dimensional Statistics, Foundations Of Computer
Science (FOCS) 2024.
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis,
Christos Tzamos, Nikos Zarifis Agnostically
Learning Multi-index Models with Queries, Foundations Of Computer
Science (FOCS) 2024.
- Ilias Diakonikolas, Daniel M. Kane Efficiently Learning
One-Hidden-Layer ReLU Networks via Schur Polynomials, Conference on Learning
Theory (COLT)
2024.
- Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos
Zarifis Statistical
Query Lower Bounds for Learning Truncated Gaussians, Conference on Learning
Theory (COLT)
2024.
- Ilias Diakonikolas, Daniel M Kane, Sihan Liu, Nikos Zarifis
Testable Learning of General Halfspaces with Adversarial
Label Noise, Conference
on Learning Theory (COLT) 2024.
- Yuqian Cheng, Daniel M. Kane, Zhicheng Zheng New
Lower Bounds for Testing Monotonicity and Log Concavity of
Distributions, Conference
on Learning Theory (COLT) 2024.
- Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit
Pensia, Thanasis Pittas Robust
Sparse Estimation for Gaussians with Optimal Error under
Huber Contamination, International Conference on
Machine Learning (ICML) 2024.
- Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan
Liu, Nikos Zarifis Super
Non-singular Decompositions of Polynomials and their
Application to Robustly Learning Low-degree PTFs, Symposium
on Theory of Computation (STOC) 2024.
- Ilias Diakonikolas, Daniel M. Kane, Sihan Liu Testing
Closeness of Multivariate Distributions via Ramsey Theory,
Symposium on Theory of Computation (STOC) 2024.
- Daniel M. Kane, Anthony Ostuni, Kewen Wu Locality
Bounds for Sampling Hamming Slices, Symposium on
Theory of Computation (STOC) 2024.
- Daniel M. Kane, Ilias Diakonikolas, Hanshen Xiao, Sihan Liu
Online
Robust Mean Estimation, Symposium on Discrete
Algorithms (SODA) 2024.
- Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun SQ
Lower Bounds for Learning Mixtures of Linear Classifiers,
Advances in Neural Information Processing Systems
(NeurIPS) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren, Yuxin Sun SQ
Lower Bounds for Non-Gaussian Component Analysis with Weaker
Assumptions, Advances in Neural Information
Processing Systems (NeurIPS) 2023.
- Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis
Pittas Near-Optimal
Algorithms for Gaussians with Huber Contamination: Mean
Estimation and Linear Regression, Advances in Neural
Information Processing Systems (NeurIPS) 2023.
- 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, Journal version TheoretiCS,
Vol 3 (2024).
- 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, 2021.
- 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.
- Daniel Kane, Andreas Fackler, Adam Gągol, Damian Straszak, Highway:
Efficient Consensus with Flexible Finality, in
preparation.
- 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 PRGs for PTFs based on the Replacement Method AIM Workshop on Low-degree polynomial methods in average-case complexity, December 2024.
- 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:
- Instructor for
CSE 291 (Introduction to robust statistics) at UCSD (Fall
2023)
- 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, Fall 2023, Fall 2024)
- 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, Fall 2024)
- 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) 2018-2024,
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