Papers
4,025 papers found
Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization
Guodong Zhang, Yuanhao Wang, Laurent Lessard et al.
Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs
Jiafan He, Dongruo Zhou, Quanquan Gu
Near-Optimal Task Selection for Meta-Learning with Mutual Information and Online Variational Bayesian Unlearning
Yizhou Chen, Shizhuo Zhang, Bryan Kian Hsiang Low
Neural Contextual Bandits without Regret
Parnian Kassraie, Andreas Krause
Neural Enhanced Dynamic Message Passing
Fei Gao, Jiang Zhang, Yan Zhang
Neural score matching for high-dimensional causal inference
Oscar Clivio, Fabian Falck, Brieuc Lehmann et al.
New Coresets for Projective Clustering and Applications
Murad Tukan, Xuan Wu, Samson Zhou et al.
Node Feature Kernels Increase Graph Convolutional Network Robustness
Mohamed El Amine Seddik, Changmin Wu, Johannes F. Lutzeyer et al.
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably
Tianyi Liu, Yan Li, Enlu Zhou et al.
Nonparametric Relational Models with Superrectangulation
Masahiro Nakano, Ryo Nishikimi, Yasuhiro Fujiwara et al.
Non-separable Spatio-temporal Graph Kernels via SPDEs
Alexander V. Nikitin, St John, Arno Solin et al.
Nonstationary multi-output Gaussian processes via harmonizable spectral mixtures
Matias Altamirano, Felipe Tobar
Non-stationary Online Learning with Memory and Non-stochastic Control
Peng Zhao, Yu-Xiang Wang, Zhi-Hua Zhou
Nonstochastic Bandits and Experts with Arm-Dependent Delays
Dirk Van Der Hoeven, Nicolò Cesa-Bianchi
Norm-Agnostic Linear Bandits
Spencer B. Gales, Sunder Sethuraman, Kwang-Sung Jun
Nuances in Margin Conditions Determine Gains in Active Learning
Samory Kpotufe, Gan Yuan, Yunfan Zhao
Obtaining Causal Information by Merging Datasets with MAXENT
Sergio H. Garrido Mejia, Elke Kirschbaum, Dominik Janzing
Offline Policy Selection under Uncertainty
Mengjiao Yang, Bo Dai, Ofir Nachum et al.
Off-Policy Risk Assessment for Markov Decision Processes
Audrey Huang, Liu Leqi, Zachary Lipton et al.
On a Connection Between Fast and Sparse Oblivious Subspace Embeddings
Rui Wang, Wangli Xu
On Combining Bags to Better Learn from Label Proportions
Rishi Saket, Aravindan Raghuveer, Balaraman Ravindran
On Convergence of Lookahead in Smooth Games
Junsoo Ha, Gunhee Kim
On Coresets for Fair Regression and Individually Fair Clustering
Rachit Chhaya, Anirban Dasgupta, Jayesh Choudhari et al.
On Distributionally Robust Optimization and Data Rebalancing
Agnieszka Słowik, Leon Bottou
One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation
Hajime Ono, Kazuhiro Minami, Hideitsu Hino