Papers
Rate of Model Collapse in Recursive Training
Ananda Theertha Suresh, Andrew Thangaraj, Aditya Nanda Kishore Khandavally
Recurrent Neural Goodness-of-Fit Test for Time Series
Aoran Zhang, Wenbin Zhou, Liyan Xie et al.
Recursive Learning of Asymptotic Variational Objectives
Alessandro Mastrototaro, Mathias Müller, Jimmy Olsson
Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation
Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut et al.
Regularity in Canonicalized Models: A Theoretical Perspective
Behrooz Tahmasebi, Stefanie Jegelka
Reinforcement Learning for Adaptive MCMC
Congye Wang, Wilson Ye Chen, Heishiro Kanagawa et al.
Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs
Kihyuk Hong, Woojin Chae, Yufan Zhang et al.
Reinforcement Learning with Intrinsically Motivated Feedback Graph for Lost-sales Inventory Control
Zifan LIU, Xinran Li, Shibo Chen et al.
Relating Piecewise Linear Kolmogorov Arnold Networks to ReLU Networks
Nandi Schoots, Mattia Jacopo Villani, Niels uit de Bos
Reliable and Scalable Variable Importance Estimation via Warm-start and Early Stopping
Zexuan Sun, Garvesh Raskutti
Restructuring Tractable Probabilistic Circuits
Honghua Zhang, Benjie Wang, Marcelo Arenas et al.
Rethinking Neural-based Matrix Inversion: Why can’t, and Where can
Yuliang Ji, Jian Wu, Yuanzhe Xi
RetroDiff: Retrosynthesis as Multi-stage Distribution Interpolation
Yiming Wang, Yuxuan Song, Yiqun Wang et al.
Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis
Ruichen Luo, Sebastian U Stich, Samuel Horváth et al.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel–Young Loss Perspective and Gap-Dependent Regret Analysis
Shinsaku Sakaue, Han Bao, Taira Tsuchiya
Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits
Brian M Cho, Dominik Meier, Kyra Gan et al.
Riemann$^2$: Learning Riemannian Submanifolds from Riemannian Data
Leonel Rozo, Miguel González-Duque, Noémie Jaquier et al.
Risk-sensitive Bandits: Arm Mixture Optimality and Regret-efficient Algorithms
Meltem Tatlı, Arpan Mukherjee, Prashanth L. A. et al.
Robust Classification by Coupling Data Mollification with Label Smoothing
Markus Heinonen, Ba-Hien Tran, Michael Kampffmeyer et al.
Robust Estimation in metric spaces: Achieving Exponential Concentration with a Fréchet Median
Jakwang Kim, Jiyoung Park, Anirban Bhattacharya
Robust Fair Clustering with Group Membership Uncertainty Sets
Sharmila Duppala, Juan Luque, John P Dickerson et al.
Robust Gradient Descent for Phase Retrieval
Alex Buna, Patrick Rebeschini
Robust Kernel Hypothesis Testing under Data Corruption
Antonin Schrab, Ilmun Kim