Papers
Near-Optimal Correlation Clustering with Privacy
Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi et al.
Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments
Liyu Chen, Haipeng Luo
Near-Optimal Multi-Agent Learning for Safe Coverage Control
Manish Prajapat, Matteo Turchetta, Melanie Zeilinger et al.
Near-Optimal No-Regret Learning Dynamics for General Convex Games
Gabriele Farina, Ioannis Anagnostides, Haipeng Luo et al.
Near-Optimal Private and Scalable $k$-Clustering
Vincent Cohen-Addad, Alessandro Epasto, Vahab Mirrokni et al.
Near-Optimal Randomized Exploration for Tabular Markov Decision Processes
Zhihan Xiong, Ruoqi Shen, Qiwen Cui et al.
Near-Optimal Regret Bounds for Multi-batch Reinforcement Learning
Zihan Zhang, Yuhang Jiang, Yuan Zhou et al.
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback
Tiancheng Jin, Tal Lancewicki, Haipeng Luo et al.
Near-Optimal Sample Complexity Bounds for Constrained MDPs
Sharan Vaswani, Lin Yang, Csaba Szepesvari
NeMF: Neural Motion Fields for Kinematic Animation
Chengan He, Jun Saito, James Zachary et al.
NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning
Rong-Jun Qin, Xingyuan Zhang, Songyi Gao et al.
Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization
Junchi YANG, Xiang Li, Niao He
Network change point localisation under local differential privacy
Mengchu Li, Tom Berrett, Yi Yu
NeuForm: Adaptive Overfitting for Neural Shape Editing
Connor Lin, Niloy Mitra, Gordon Wetzstein et al.
NeuPhysics: Editable Neural Geometry and Physics from Monocular Videos
Yi-Ling Qiao, Alexander Gao, Ming Lin
Neur2SP: Neural Two-Stage Stochastic Programming
Rahul Mihir Patel, Justin Dumouchelle, Elias Khalil et al.
Neural Abstractions
Alessandro Abate, Alec Edwards, Mirco Giacobbe
Neural Approximation of Graph Topological Features
Zuoyu Yan, Tengfei Ma, Liangcai Gao et al.
Neural Attentive Circuits
Martin Weiss, Nasim Rahaman, Francesco Locatello et al.
Neural Basis Models for Interpretability
Filip Radenovic, Abhimanyu Dubey, Dhruv Mahajan
Neural Circuit Architectural Priors for Embodied Control
Nikhil Bhattasali, Anthony M Zador, Tatiana Engel
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold
Can Yaras, Peng Wang, Zhihui Zhu et al.
Neural Conservation Laws: A Divergence-Free Perspective
Jack Richter-Powell, Yaron Lipman, Ricky T. Q. Chen
Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules
Kazuki Irie, Francesco Faccio, Jürgen Schmidhuber
Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection
Abir De, Soumen Chakrabarti