Kane, Daniel

48 publications

NeurIPS 2025 Algorithms and SQ Lower Bounds for Robustly Learning Real-Valued Multi-Index Models Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane, Lisheng Ren

ICML 2025 Batch List-Decodable Linear Regression via Higher Moments Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Sihan Liu, Thanasis Pittas

ALT 2025 Do PAC-Learners Learn the Marginal Distribution? Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan

ICML 2025 Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane, Thanasis Pittas

NeurIPS 2025 Information-Computation Tradeoffs for Noiseless Linear Regression with Oblivious Contamination Ilias Diakonikolas, Chao Gao, Daniel Kane, John Lafferty, Ankit Pensia

ICML 2025 On Fine-Grained Distinct Element Estimation Ilias Diakonikolas, Daniel Kane, Jasper C.H. Lee, Thanasis Pittas, David Woodruff, Samson Zhou

ICML 2025 On Learning Parallel Pancakes with Mostly Uniform Weights Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Jasper C.H. Lee, Thanasis Pittas

NeurIPS 2025 Replicable Distribution Testing Ilias Diakonikolas, Jingyi Gao, Daniel Kane, Sihan Liu, Christopher Ye

NeurIPS 2025 Robust Regression of General ReLUs with Queries Ilias Diakonikolas, Daniel Kane, Mingchen Ma

COLT 2024 New Lower Bounds for Testing Monotonicity and Log Concavity of Distributions Yuqian Cheng, Daniel Kane, Zheng Zhicheng

ICML 2024 Robust Sparse Estimation for Gaussians with Optimal Error Under Huber Contamination Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas

COLT 2024 Testable Learning of General Halfspaces with Adversarial Label Noise Ilias Diakonikolas, Daniel Kane, Sihan Liu, Nikos Zarifis

COLT 2023 A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points Daniel Kane, Ilias Diakonikolas

NeurIPS 2023 A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm Ilias Diakonikolas, Daniel Kane, Jasper Lee, Ankit Pensia, Thanasis Pittas

NeurIPS 2023 Efficient Testable Learning of Halfspaces with Adversarial Label Noise Ilias Diakonikolas, Daniel Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis

COLT 2023 Exponential Hardness of Reinforcement Learning with Linear Function Approximation Sihan Liu, Gaurav Mahajan, Daniel Kane, Shachar Lovett, Gellért Weisz, Csaba Szepesvári

NeurIPS 2023 Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas

NeurIPS 2023 Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis

ICML 2023 Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression Under Gaussian Marginals Ilias Diakonikolas, Daniel Kane, Lisheng Ren

ICML 2023 Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas

NeurIPS 2023 SQ Lower Bounds for Learning Mixtures of Linear Classifiers Ilias Diakonikolas, Daniel Kane, Yuxin Sun

NeurIPS 2023 SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun

AISTATS 2022 Hardness of Learning a Single Neuron with Adversarial Label Noise Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren

COLT 2022 Computational-Statistical Gap in Reinforcement Learning Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan

NeurIPS 2022 Cryptographic Hardness of Learning Halfspaces with Massart Noise Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren

NeurIPS 2022 List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas

COLT 2022 Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise Ilias Diakonikolas, Daniel Kane

NeurIPS 2022 Nearly-Tight Bounds for Testing Histogram Distributions Clément L Canonne, Ilias Diakonikolas, Daniel Kane, Sihan Liu

COLT 2022 Non-Gaussian Component Analysis via Lattice Basis Reduction Ilias Diakonikolas, Daniel Kane

NeurIPS 2022 Outlier-Robust Sparse Estimation via Non-Convex Optimization Yu Cheng, Ilias Diakonikolas, Rong Ge, Shivam Gupta, Daniel Kane, Mahdi Soltanolkotabi

NeurIPS 2022 Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions Ilias Diakonikolas, Daniel Kane, Jasper Lee, Ankit Pensia

NeurIPS 2022 SQ Lower Bounds for Learning Single Neurons with Massart Noise Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun

AISTATS 2021 vqSGD: Vector Quantized Stochastic Gradient Descent Venkata Gandikota, Daniel Kane, Raj Kumar Maity, Arya Mazumdar

COLT 2021 Bounded Memory Active Learning Through Enriched Queries Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz

NeurIPS 2021 Forster Decomposition and Learning Halfspaces with Noise Ilias Diakonikolas, Daniel Kane, Christos Tzamos

NeurIPS 2021 List-Decodable Mean Estimation in Nearly-PCA Time Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian

NeurIPS 2021 Statistical Query Lower Bounds for List-Decodable Linear Regression Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas, Alistair Stewart

NeurIPS 2020 List-Decodable Mean Estimation via Iterative Multi-Filtering Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard

NeurIPS 2020 Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs Under Gaussian Marginals Ilias Diakonikolas, Daniel Kane, Nikos Zarifis

COLT 2020 Noise-Tolerant, Reliable Active Classification with Comparison Queries Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan

NeurIPS 2020 The Power of Comparisons for Actively Learning Linear Classifiers Max Hopkins, Daniel Kane, Shachar Lovett

NeurIPS 2019 Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi

COLT 2019 On Communication Complexity of Classification Problems Daniel Kane, Roi Livni, Shay Moran, Amir Yehudayoff

NeurIPS 2019 Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ecprice, Alistair Stewart

NeurIPS 2019 Private Testing of Distributions via Sample Permutations Maryam Aliakbarpour, Ilias Diakonikolas, Daniel Kane, Ronitt Rubinfeld

ICML 2019 Sever: A Robust Meta-Algorithm for Stochastic Optimization Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart

COLT 2019 The Optimal Approximation Factor in Density Estimation Olivier Bousquet, Daniel Kane, Shay Moran

NeurIPS 2018 Robust Learning of Fixed-Structure Bayesian Networks Yu Cheng, Ilias Diakonikolas, Daniel Kane, Alistair Stewart