Papers
On the Role of Discount Factor in Offline Reinforcement Learning
Hao Hu, Yiqin Yang, Qianchuan Zhao et al.
On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs
Yuanzhou Chen, Jiafan He, Quanquan Gu
On the Statistical Benefits of Curriculum Learning
Ziping Xu, Ambuj Tewari
On the Surrogate Gap between Contrastive and Supervised Losses
Han Bao, Yoshihiro Nagano, Kento Nozawa
On Transportation of Mini-batches: A Hierarchical Approach
Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen et al.
On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation
Xiaohong Chen, Zhengling Qi
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets
Hongxin Wei, Lue Tao, Renchunzi Xie et al.
Optimal Algorithms for Mean Estimation under Local Differential Privacy
Hilal Asi, Vitaly Feldman, Kunal Talwar
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization
Wei Jiang, Bokun Wang, Yibo Wang et al.
Optimal and Efficient Dynamic Regret Algorithms for Non-Stationary Dueling Bandits
Aadirupa Saha, Shubham Gupta
Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training
Charbel Sakr, Steve Dai, Rangha Venkatesan et al.
Optimal Clustering with Noisy Queries via Multi-Armed Bandit
Jinghui Xia, Zengfeng Huang
Optimal Estimation of Policy Gradient via Double Fitted Iteration
Chengzhuo Ni, Ruiqi Zhang, Xiang Ji et al.
Optimally Controllable Perceptual Lossy Compression
Zeyu Yan, Fei Wen, Peilin Liu
Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer
Lucas Nunes Alegre, Ana Bazzan, Bruno C. Da Silva
Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training
Risheng Liu, Xuan Liu, Shangzhi Zeng et al.
Optimization-Induced Graph Implicit Nonlinear Diffusion
Qi Chen, Yifei Wang, Yisen Wang et al.
Optimizing Sequential Experimental Design with Deep Reinforcement Learning
Tom Blau, Edwin V. Bonilla, Iadine Chades et al.
Optimizing Tensor Network Contraction Using Reinforcement Learning
Eli Meirom, Haggai Maron, Shie Mannor et al.
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering
Ekdeep Lubana, Chi Ian Tang, Fahim Kawsar et al.
Order Constraints in Optimal Transport
Yu Chin Fabian Lim, Laura Wynter, Shiau Hong Lim
Out-of-Distribution Detection with Deep Nearest Neighbors
Yiyou Sun, Yifei Ming, Xiaojin Zhu et al.
Overcoming Oscillations in Quantization-Aware Training
Markus Nagel, Marios Fournarakis, Yelysei Bondarenko et al.
PAC-Bayesian Bounds on Rate-Efficient Classifiers
Alhabib Abbas, Yiannis Andreopoulos
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs
Zehao Dong, Muhan Zhang, Fuhai Li et al.