Daniel M. Kane
CV
(Last updated 9/25/2024)
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.
- Ery Arias-Castro,
Clement Berenfeld, Daniel
Kane Theoretical
Foundations of Ordinal
Multidimensional
Scaling, Including
Internal and External
Unfolding, in
preparation.
- 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 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) 2018-2024,
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