Papers
1,396 papers found
On the well-spread property and its relation to linear regression
Hongjie Chen, Tommaso d’Orsi
Open Problem: Better Differentially Private Learning Algorithms with Margin Guarantees
Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
Open Problem: Do you pay for Privacy in Online learning?
Amartya Sanyal, Giorgia Ramponi
Open Problem: Finite-Time Instance Dependent Optimality for Stochastic Online Learning with Feedback Graphs
Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert
Open Problem: Properly learning decision trees in polynomial time?
Guy Blanc, Jane Lange, Mingda Qiao et al.
Open Problem: Running time complexity of accelerated $\ell_1$-regularized PageRank
Kimon Fountoulakis, Shenghao Yang
Optimal and instance-dependent guarantees for Markovian linear stochastic approximation
Wenlong Mou, Ashwin Pananjady, Martin Wainwright et al.
Optimal Mean Estimation without a Variance
Yeshwanth Cherapanamjeri, Nilesh Tripuraneni, Peter Bartlett et al.
Optimal SQ Lower Bounds for Learning Halfspaces with Massart Noise
Rajai Nasser, Stefan Tiegel
Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models
Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun
Optimization-Based Separations for Neural Networks
Itay Safran, Jason Lee
Orthogonal Statistical Learning with Self-Concordant Loss
Lang Liu, Carlos Cinelli, Zaid Harchaoui
Parameter-free Mirror Descent
Andrew Jacobsen, Ashok Cutkosky
Policy Optimization for Stochastic Shortest Path
Liyu Chen, Haipeng Luo, Aviv Rosenberg
Private and polynomial time algorithms for learning Gaussians and beyond
Hassan Ashtiani, Christopher Liaw
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
Private High-Dimensional Hypothesis Testing
Shyam Narayanan
Private Matrix Approximation and Geometry of Unitary Orbits
Oren Mangoubi, Yikai Wu, Satyen Kale et al.
Private Robust Estimation by Stabilizing Convex Relaxations
Pravesh Kothari, Pasin Manurangsi, Ameya Velingker
Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States
Julian Zimmert, Naman Agarwal, Satyen Kale
Random Graph Matching in Geometric Models: the Case of Complete Graphs
Haoyu Wang, Yihong Wu, Jiaming Xu et al.
Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms
Milad Sefidgaran, Amin Gohari, Gaël Richard et al.