Daniel M. Kane
CV
(Last updated 4/1/2024)
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, Jasper C. H. Lee, Thanasis Pittas Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation, 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.
- Yuqian Cheng, Daniel M. Kane, Zhicheng Zheng New
Lower Bounds for Testing Monotonicity and Log Concavity of
Distributions, in preparation.
- Ery Arias-Castro, Clement Berenfeld, Daniel Kane Theoretical
Foundations of Ordinal Multidimensional Scaling, Including
Internal and External Unfolding, in preparation.
- 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, to appear.
- Ilias Diakonikolas, Daniel M. Kane, Sihan Liu Testing Closeness of Multivariate Distributions via Ramsey Theory, Symposium
on Theory of Computation (STOC) 2024, to appear.
- Daniel M. Kane, Anthony Ostuni, Kewen Wu Locality Bounds for Sampling Hamming Slices, Symposium
on Theory of Computation (STOC) 2024, to appear.
- 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 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)
- 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