← Authors

Daniel Kane

45 papers · 2013–2025 · 5 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (8) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (11) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (38) 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (12) 🏠 Conference Loyalist (22) πŸ”¬ Deep Specialist (21) 🀝 Dynamic Duo (34) πŸ—ƒοΈ Keyword Collector (128) ❓ The Questioner ⚑ Prolific Year (10) πŸ’Ž Century Club (45) πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter

Conferences

NIPS (22) COLT (12) ICML (8) AISTATS (2) ALT (1)

Top co-authors

Ilias Diakonikolas (34) Thanasis Pittas (10) Ankit Pensia (7) Sihan Liu (6) Shachar Lovett (6) Sushrut Karmalkar (5) Lisheng Ren (5) Max Hopkins (4) Nikos Zarifis (4) Gaurav Mahajan (4)

Research topics

Differential Privacy (1) Statistics (1)

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