Papers
4,025 papers found
Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow
Yinuo Ren, Tesi Xiao, Tanmay Gangwani et al.
Multi-Resolution Active Learning of Fourier Neural Operators
Shibo Li, Xin Yu, Wei Xing et al.
Multi-resolution Time-Series Transformer for Long-term Forecasting
Yitian Zhang, Liheng Ma, Soumyasundar Pal et al.
Multitask Online Learning: Listen to the Neighborhood Buzz
Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue
Multivariate Time Series Forecasting By Graph Attention Networks With Theoretical Guarantees
Zhi Zhang, Weijian Li, Han Liu
Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization
Yutong Wang, Rishi Sonthalia, Wei Hu
Near-Optimal Convex Simple Bilevel Optimization with a Bisection Method
Jiulin Wang, Xu Shi, Rujun Jiang
Near-optimal Per-Action Regret Bounds for Sleeping Bandits
Quan M. Nguyen, Nishant Mehta
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games
Yang Cai, Haipeng Luo, Chen-Yu Wei et al.
Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits
Arnab Maiti, Ross Boczar, Kevin Jamieson et al.
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean
Anton Frederik Thielmann, René-Marcel Kruse, Thomas Kneib et al.
Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes
Haoming Yang, Ali Hasan, Yuting Ng et al.
NoisyMix: Boosting Model Robustness to Common Corruptions
Benjamin Erichson, Soon Hoe Lim, Winnie Xu et al.
Non-Convex Joint Community Detection and Group Synchronization via Generalized Power Method
Sijin Chen, Xiwei Cheng, Anthony Man-Cho So
Non-Neighbors Also Matter to Kriging: A New Contrastive-Prototypical Learning
Zhishuai Li, Yunhao Nie, Ziyue Li et al.
Nonparametric Automatic Differentiation Variational Inference with Spline Approximation
Yuda Shao, Shan N Yu, Tianshu Feng
Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks
Waleed Mustafa, Philipp Liznerski, Antoine Ledent et al.
No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints
Arpan Losalka, Jonathan Scarlett
Offline Policy Evaluation and Optimization Under Confounding
Chinmaya Kausik, Yangyi Lu, Kevin Tan et al.
Offline Primal-Dual Reinforcement Learning for Linear MDPs
Germano Gabbianelli, Gergely Neu, Matteo Papini et al.
On Convergence in Wasserstein Distance and f-divergence Minimization Problems
Cheuk Ting Li, Jingwei Zhang, Farzan Farnia
On Counterfactual Metrics for Social Welfare: Incentives, Ranking, and Information Asymmetry
Serena Wang, Stephen Bates, P Aronow et al.
On cyclical MCMC sampling
Liwei Wang, Xinru Liu, Aaron Smith et al.
On-Demand Federated Learning for Arbitrary Target Class Distributions
Isu Jeong, Seulki Lee