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Daniel M. Kane

26 papers · 2017–2025 · 4 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+9 more ↓ πŸƒ Academic Marathon (8) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (4) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (7)
🐝 Cross-Pollinator (7) πŸ—ΊοΈ Taxonomy Completionist (30) πŸ† Keyword Champion (2) 🀝 Dynamic Duo (23) πŸ”¬ Deep Specialist (11) πŸ’Ž Century Club (26) πŸ—ƒοΈ Keyword Collector (105) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (9)

Conferences

COLT (19) NIPS (4) ICML (2) AISTATS (1)

Research topics

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 Dobrushin’s 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