Papers
4,025 papers found
On the Capacity Limits of Privileged ERM
Michal Sharoni, Sivan Sabato
On the Complexity of Representation Learning in Contextual Linear Bandits
Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
On the Consistency Rate of Decision Tree Learning Algorithms
Qin-Cheng Zheng, Shen-Huan Lyu, Shao-Qun Zhang et al.
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network
Hongchang Gao, Bin Gu, My T. Thai
On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation
Anna Winnicki, R. Srikant
On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data
Tina Behnia, Ganesh Ramachandra Kini, Vala Vakilian et al.
On the Limitations of the Elo, Real-World Games are Transitive, not Additive
Quentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel
On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks
Hongru Yang, Zhangyang Wang
On the Privacy Risks of Algorithmic Recourse
Martin Pawelczyk, Himabindu Lakkaraju, Seth Neel
On the Strategyproofness of the Geometric Median
El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui et al.
On Universal Portfolios with Continuous Side Information
Alankrita Bhatt, J. Jon Ryu, Young-Han Kim
Optimal Algorithms for Latent Bandits with Cluster Structure
Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam et al.
Optimal and Private Learning from Human Response Data
Duc Nguyen, Anderson Ye Zhang
Optimal Contextual Bandits with Knapsacks under Realizability via Regression Oracles
Yuxuan Han, Jialin Zeng, Yang Wang et al.
Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems
Nicolas Christianson, Junxuan Shen, Adam Wierman
Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition
Qian Yu, Yining Wang, Baihe Huang et al.
Optimal Sketching Bounds for Sparse Linear Regression
Tung Mai, Alexander Munteanu, Cameron Musco et al.
Optimism and Delays in Episodic Reinforcement Learning
Benjamin Howson, Ciara Pike-Burke, Sarah Filippi
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach
Yunzhe Zhou, Zhengling Qi, Chengchun Shi et al.
Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path
Muhammad Aneeq Uz Zaman, Alec Koppel, Sujay Bhatt et al.
Origins of Low-Dimensional Adversarial Perturbations
Elvis Dohmatob, Chuan Guo, Morgane Goibert
Overcoming Prior Misspecification in Online Learning to Rank
Javad Azizi, Ofer Meshi, Masrour Zoghi et al.
Overparameterized Random Feature Regression with Nearly Orthogonal Data
Zhichao Wang, Yizhe Zhu
PAC-Bayesian Learning of Optimization Algorithms
Michael Sucker, Peter Ochs