Papers
8,340 papers found
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.
Reliable Measures of Spread in High Dimensional Latent Spaces
Anna Marbut, Katy Mckinney-Bock, Travis Wheeler
ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs
Ted Moskovitz, Brendan O’Donoghue, Vivek Veeriah et al.
Reparameterized Policy Learning for Multimodal Trajectory Optimization
Zhiao Huang, Litian Liang, Zhan Ling et al.
Repository-Level Prompt Generation for Large Language Models of Code
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
Representation-Driven Reinforcement Learning
Ofir Nabati, Guy Tennenholtz, Shie Mannor
Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
Zakaria Mhammedi, Dylan J Foster, Alexander Rakhlin
Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
Yash Chandak, Shantanu Thakoor, Zhaohan Daniel Guo et al.
Representer Point Selection for Explaining Regularized High-dimensional Models
Che-Ping Tsai, Jiong Zhang, Hsiang-Fu Yu et al.
Reprogramming Pretrained Language Models for Antibody Sequence Infilling
Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen et al.
Restoration based Generative Models
Jaemoo Choi, Yesom Park, Myungjoo Kang
Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-type Samplers
Sitan Chen, Giannis Daras, Alex Dimakis
Resurrecting Recurrent Neural Networks for Long Sequences
Antonio Orvieto, Samuel L Smith, Albert Gu et al.
Rethink DARTS Search Space and Renovate a New Benchmark
Jiuling Zhang, Zhiming Ding
Rethinking Backdoor Attacks
Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov et al.
Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching
Fang Wu, Siyuan Li, Xurui Jin et al.