Papers
Recovery of Sparse Signals from a Mixture of Linear Samples
Soumyabrata Pal, Arya Mazumdar
Recurrent Hierarchical Topic-Guided RNN for Language Generation
Dandan Guo, Bo Chen, Ruiying Lu et al.
Reducing Sampling Error in Batch Temporal Difference Learning
Brahma Pavse, Ishan Durugkar, Josiah Hanna et al.
Refined bounds for algorithm configuration: The knife-edge of dual class approximability
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Regularized Optimal Transport is Ground Cost Adversarial
François-Pierre Paty, Marco Cuturi
Reinforcement Learning for Integer Programming: Learning to Cut
Yunhao Tang, Shipra Agrawal, Yuri Faenza
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
Gregor Simm, Robert Pinsler, Jose Miguel Hernandez-Lobato
Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
Lin Yang, Mengdi Wang
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
Rob Cornish, Anthony Caterini, George Deligiannidis et al.
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce, Matthias Hein
Reliable Fidelity and Diversity Metrics for Generative Models
Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh et al.
Representation Learning via Adversarially-Contrastive Optimal Transport
Anoop Cherian, Shuchin Aeron
Representations for Stable Off-Policy Reinforcement Learning
Dibya Ghosh, Marc G. Bellemare
Representing Unordered Data Using Complex-Weighted Multiset Automata
Justin DeBenedetto, David Chiang
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods
Adam Stooke, Joshua Achiam, Pieter Abbeel
Restarted Bayesian Online Change-point Detector achieves Optimal Detection Delay
Reda Alami, Odalric Maillard, Raphael Feraud
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
Zitong Yang, Yaodong Yu, Chong You et al.
Retrieval Augmented Language Model Pre-Training
Kelvin Guu, Kenton Lee, Zora Tung et al.
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search
Binghong Chen, Chengtao Li, Hanjun Dai et al.
Reverse-engineering deep ReLU networks
David Rolnick, Konrad Kording
Revisiting Fundamentals of Experience Replay
William Fedus, Prajit Ramachandran, Rishabh Agarwal et al.
Revisiting Spatial Invariance with Low-Rank Local Connectivity
Gamaleldin Elsayed, Prajit Ramachandran, Jonathon Shlens et al.
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning
Karsten Roth, Timo Milbich, Samarth Sinha et al.