Papers
Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
Shariq Iqbal, Christian A Schroeder De Witt, Bei Peng et al.
Randomized Exploration in Reinforcement Learning with General Value Function Approximation
Haque Ishfaq, Qiwen Cui, Viet Nguyen et al.
Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning
Hassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei et al.
RATT: Leveraging Unlabeled Data to Guarantee Generalization
Saurabh Garg, Sivaraman Balakrishnan, Zico Kolter et al.
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
Haitian Sun, Patrick Verga, Bhuwan Dhingra et al.
Recomposing the Reinforcement Learning Building Blocks with Hypernetworks
Elad Sarafian, Shai Keynan, Sarit Kraus
Recovering AES Keys with a Deep Cold Boot Attack
Itamar Zimerman, Eliya Nachmani, Lior Wolf
Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
Xinlei Yi, Xiuxian Li, Tao Yang et al.
Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach
Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher
Regularized Online Allocation Problems: Fairness and Beyond
Santiago Balseiro, Haihao Lu, Vahab Mirrokni
Regularized Submodular Maximization at Scale
Ehsan Kazemi, Shervin Minaee, Moran Feldman et al.
Regularizing towards Causal Invariance: Linear Models with Proxies
Michael Oberst, Nikolaj Thams, Jonas Peters et al.
Reinforcement Learning for Cost-Aware Markov Decision Processes
Wesley Suttle, Kaiqing Zhang, Zhuoran Yang et al.
Reinforcement Learning of Implicit and Explicit Control Flow Instructions
Ethan Brooks, Janarthanan Rajendran, Richard L Lewis et al.
Reinforcement Learning Under Moral Uncertainty
Adrien Ecoffet, Joel Lehman
Reinforcement Learning with Prototypical Representations
Denis Yarats, Rob Fergus, Alessandro Lazaric et al.
Relative Deviation Margin Bounds
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh
Relative Positional Encoding for Transformers with Linear Complexity
Antoine Liutkus, Ondřej Cı́fka, Shih-Lun Wu et al.
REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung et al.
Representational aspects of depth and conditioning in normalizing flows
Frederic Koehler, Viraj Mehta, Andrej Risteski
Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data
Esther Rolf, Theodora T Worledge, Benjamin Recht et al.
Representation Matters: Offline Pretraining for Sequential Decision Making
Mengjiao Yang, Ofir Nachum
Representation Subspace Distance for Domain Adaptation Regression
Xinyang Chen, Sinan Wang, Jianmin Wang et al.
Reserve Price Optimization for First Price Auctions in Display Advertising
Zhe Feng, Sebastien Lahaie, Jon Schneider et al.
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica et al.