Papers
Reining Generalization in Offline Reinforcement Learning via Representation Distinction
Yi Ma, Hongyao Tang, Dong Li et al.
Relative Entropic Optimal Transport: a (Prior-aware) Matching Perspective to (Unbalanced) Classification
Liangliang Shi, Haoyu Zhen, Gu Zhang et al.
Relax, it doesn’t matter how you get there: A new self-supervised approach for multi-timescale behavior analysis
Mehdi Azabou, Michael Mendelson, Nauman Ahad et al.
Reliable learning in challenging environments
Maria-Florina F Balcan, Steve Hanneke, Rattana Pukdee et al.
Reliable Off-Policy Learning for Dosage Combinations
Jonas Schweisthal, Dennis Frauen, Valentyn Melnychuk et al.
ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation
Shuyang Sun, WEIJUN WANG, Andrew Howard et al.
Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach
Haoxuan Li, Kunhan Wu, Chunyuan Zheng et al.
RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars
Dongwei Pan, Long Zhuo, Jingtan Piao et al.
Renku: a platform for sustainable data science
Rok Roškar, Chandrasekhar Ramakrishnan, Michele Volpi et al.
Repetition In Repetition Out: Towards Understanding Neural Text Degeneration from the Data Perspective
Huayang Li, Tian Lan, Zihao Fu et al.
Replicability in Reinforcement Learning
Amin Karbasi, Grigoris Velegkas, Lin Yang et al.
Replicable Clustering
Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni et al.
Replicable Reinforcement Learning
Eric Eaton, Marcel Hussing, Michael J. Kearns et al.
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability
Chuning Zhu, Max Simchowitz, Siri Gadipudi et al.
Representational Strengths and Limitations of Transformers
Clayton Sanford, Daniel J. Hsu, Matus J. Telgarsky
Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning
Francesca Bartolucci, Emmanuel de Bézenac, Bogdan Raonic et al.
Representation Learning via Consistent Assignment of Views over Random Partitions
Thalles Santos Silva, Adín Ramírez Rivera
Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests
Edward Raff, James Holt
Resetting the Optimizer in Deep RL: An Empirical Study
Kavosh Asadi, Rasool Fakoor, Shoham Sabach
Residual Alignment: Uncovering the Mechanisms of Residual Networks
Jianing Li, Vardan Papyan
Residual Q-Learning: Offline and Online Policy Customization without Value
Chenran Li, Chen Tang, Haruki Nishimura et al.
Resilient Constrained Learning
Ignacio Hounie, Alejandro Ribeiro, Luiz F. O. Chamon
Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis
Victor Letzelter, Mathieu Fontaine, Mickael Chen et al.
ResMem: Learn what you can and memorize the rest
Zitong Yang, MICHAL LUKASIK, Vaishnavh Nagarajan et al.