Papers
Recasting Self-Attention with Holographic Reduced Representations
Mohammad Mahmudul Alam, Edward Raff, Stella Biderman et al.
Reconstructive Neuron Pruning for Backdoor Defense
Yige Li, Xixiang Lyu, Xingjun Ma et al.
Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing
Hyeonsu Jeong, Hye Won Chung
Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework
Arman Rahbar, Ashkan Panahi, Morteza Haghir Chehreghani et al.
ReDi: Efficient Learning-Free Diffusion Inference via Trajectory Retrieval
Kexun Zhang, Xianjun Yang, William Yang Wang et al.
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
Yilun Du, Conor Durkan, Robin Strudel et al.
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs
Saro Passaro, C. Lawrence Zitnick
Refined Regret for Adversarial MDPs with Linear Function Approximation
Yan Dai, Haipeng Luo, Chen-Yu Wei et al.
Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models
Dongjun Kim, Yeongmin Kim, Se Jung Kwon et al.
Reflected Diffusion Models
Aaron Lou, Stefano Ermon
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts
Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin et al.
Regression with Label Permutation in Generalized Linear Model
Guanhua Fang, Ping Li
Regression with Sensor Data Containing Incomplete Observations
Takayuki Katsuki, Takayuki Osogami
Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents
Wenhao Xu, Xuefeng Gao, Xuedong He
Regret Minimization and Convergence to Equilibria in General-sum Markov Games
Liad Erez, Tal Lancewicki, Uri Sherman et al.
Regret-Minimizing Double Oracle for Extensive-Form Games
Xiaohang Tang, Le Cong Dinh, Stephen Marcus Mcaleer et al.
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang et al.
Regularization-free Diffeomorphic Temporal Alignment Nets
Ron Shapira Weber, Oren Freifeld
Regularizing Towards Soft Equivariance Under Mixed Symmetries
Hyunsu Kim, Hyungi Lee, Hongseok Yang et al.
Reinforcement Learning Can Be More Efficient with Multiple Rewards
Christoph Dann, Yishay Mansour, Mehryar Mohri
Reinforcement Learning from Passive Data via Latent Intentions
Dibya Ghosh, Chethan Anand Bhateja, Sergey Levine
Reinforcement Learning in Low-rank MDPs with Density Features
Audrey Huang, Jinglin Chen, Nan Jiang
Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
Anas Barakat, Ilyas Fatkhullin, Niao He
Reinforcement Learning with History Dependent Dynamic Contexts
Guy Tennenholtz, Nadav Merlis, Lior Shani et al.
Relevant Walk Search for Explaining Graph Neural Networks
Ping Xiong, Thomas Schnake, Michael Gastegger et al.