Daniel Kane
45 papers · 2013–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Conference Polyglot (5) π§ Keyword Pioneer π Academic Marathon (12) π Cross-Pollinator (11)
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(38)
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Conference Polyglot
(5)
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Academic Marathon
(12)
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Conference Loyalist
(22)
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Deep Specialist
(21)
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Dynamic Duo
(34)
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Keyword Collector
(128)
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The Questioner
β‘
Prolific Year
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Century Club
(45)
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Unstoppable
(8)
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Trend Setter
Conferences
NIPS (22)
COLT (12)
ICML (8)
AISTATS (2)
ALT (1)
Top co-authors
Research topics
Keywords
statistical query
(8)
learning theory
(8)
robust statistics
(8)
sample complexity
(7)
pac learning
(7)
gaussian distribution
(6)
outlier detection
(5)
massart noise
(5)
lower bound
(5)
halfspace learning
(4)
agnostic learning
(4)
mean estimation
(4)
total variation distance
(3)
list-decodable learning
(3)
distribution testing
(3)
adversarial label noise
(3)
sparse mean estimation
(3)
active learning
(3)
sparse estimation
(3)
statistical query lower bound
(3)
Papers
On Fine-Grained Distinct Element Estimation
ICML 2025
On Learning Parallel Pancakes with Mostly Uniform Weights
ICML 2025
Do PAC-Learners Learn the Marginal Distribution?
ALT 2025
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
ICML 2025
Batch List-Decodable Linear Regression via Higher Moments
ICML 2025
Testable Learning of General Halfspaces with Adversarial Label Noise
COLT 2024
New Lower Bounds for Testing Monotonicity and Log Concavity of Distributions
COLT 2024
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination
ICML 2024
Exponential Hardness of Reinforcement Learning with Linear Function Approximation
COLT 2023
Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals
ICML 2023
SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions
NIPS 2023
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
NIPS 2023
SQ Lower Bounds for Learning Mixtures of Linear Classifiers
NIPS 2023
Efficient Testable Learning of Halfspaces with Adversarial Label Noise
NIPS 2023
Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression
NIPS 2023
A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm
NIPS 2023
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA
ICML 2023
A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points
COLT 2023
Computational-Statistical Gap in Reinforcement Learning
COLT 2022
Hardness of Learning a Single Neuron with Adversarial Label Noise
AISTATS 2022
Cryptographic Hardness of Learning Halfspaces with Massart Noise
NIPS 2022
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions
NIPS 2022
Outlier-Robust Sparse Estimation via Non-Convex Optimization
NIPS 2022
List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering
NIPS 2022
SQ Lower Bounds for Learning Single Neurons with Massart Noise
NIPS 2022
Nearly-Tight Bounds for Testing Histogram Distributions
NIPS 2022
Non-Gaussian Component Analysis via Lattice Basis Reduction
COLT 2022
Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise
COLT 2022
vqSGD: Vector Quantized Stochastic Gradient Descent
AISTATS 2021
Statistical Query Lower Bounds for List-Decodable Linear Regression
NIPS 2021
Forster Decomposition and Learning Halfspaces with Noise
NIPS 2021
List-Decodable Mean Estimation in Nearly-PCA Time
NIPS 2021
Bounded Memory Active Learning through Enriched Queries
COLT 2021
Noise-tolerant, Reliable Active Classification with Comparison Queries
COLT 2020
Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals
NIPS 2020
List-Decodable Mean Estimation via Iterative Multi-Filtering
NIPS 2020
The Power of Comparisons for Actively Learning Linear Classifiers
NIPS 2020
Sever: A Robust Meta-Algorithm for Stochastic Optimization
ICML 2019
On Communication Complexity of Classification Problems
COLT 2019
The Optimal Approximation Factor in Density Estimation
COLT 2019
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
NIPS 2019
Private Testing of Distributions via Sample Permutations
NIPS 2019
Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin
NIPS 2019
Robust Learning of Fixed-Structure Bayesian Networks
NIPS 2018
Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching
COLT 2013