Daniel M. Kane
26 papers · 2017–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (8) π Interdisciplinary Bridge π Conference Polyglot (4) π§ Keyword Pioneer π Cross-Pollinator (7)
π
Cross-Pollinator
(7)
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Taxonomy Completionist
(30)
π
Keyword Champion
(2)
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Dynamic Duo
(23)
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Deep Specialist
(11)
π
Century Club
(26)
ποΈ
Keyword Collector
(105)
β‘
Prolific Year
(5)
π₯
Unstoppable
(9)
Conferences
COLT (19)
NIPS (4)
ICML (2)
AISTATS (1)
Top co-authors
Research topics
Keywords
sample complexity
(7)
pac learning
(5)
statistical query
(4)
mean estimation
(4)
ising model
(3)
hypothesis testing
(3)
polynomial time algorithm
(2)
streaming algorithm
(2)
relu network
(2)
outlier detection
(2)
query complexity
(2)
graphical model
(2)
robust estimation
(2)
lower bound
(2)
robust statistics
(2)
agnostic learning
(2)
high-dimensional statistics
(2)
halfspace learning
(2)
distribution testing
(2)
identity testing
(2)
Papers
Faster Algorithms for Agnostically Learning Disjunctions and their Implications
COLT 2025
Active Learning of General Halfspaces: Label Queries vs Membership Queries
NIPS 2024
Statistical Query Lower Bounds for Learning Truncated Gaussians
COLT 2024
Efficiently Learning One-Hidden-Layer ReLU Networks via SchurPolynomials
COLT 2024
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise
COLT 2023
Statistical and Computational Limits for Tensor-on-Tensor Association Detection
COLT 2023
SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians
COLT 2023
Robust Sparse Mean Estimation via Sum of Squares
COLT 2022
Coresets for Data Discretization and Sine Wave Fitting
AISTATS 2022
Realizable Learning is All You Need
COLT 2022
Streaming Algorithms for High-Dimensional Robust Statistics
ICML 2022
Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models
COLT 2022
Boosting in the Presence of Massart Noise
COLT 2021
The Sample Complexity of Robust Covariance Testing
COLT 2021
The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model
COLT 2021
Outlier-Robust Learning of Ising Models Under Dobrushinβs Condition
COLT 2021
The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise
NIPS 2020
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks
COLT 2020
Outlier Robust Mean Estimation with Subgaussian Rates via Stability
NIPS 2020
Learning Ising Models with Independent Failures
COLT 2019
Testing Identity of Multidimensional Histograms
COLT 2019
Communication and Memory Efficient Testing of Discrete Distributions
COLT 2019
Sharp Bounds for Generalized Uniformity Testing
NIPS 2018
Testing Bayesian Networks
COLT 2017
Being Robust (in High Dimensions) Can Be Practical
ICML 2017
Learning Multivariate Log-concave Distributions
COLT 2017