Papers
One Sample Stochastic Frank-Wolfe
Mingrui Zhang, Zebang Shen, Aryan Mokhtari et al.
On Generalization Bounds of a Family of Recurrent Neural Networks
Minshuo Chen, Xingguo Li, Tuo Zhao
Online Batch Decision-Making with High-Dimensional Covariates
Chi-Hua Wang, Guang Cheng
Online Binary Space Partitioning Forests
Xuhui Fan, Bin Li, Scott SIsson
Online Continuous DR-Submodular Maximization with Long-Term Budget Constraints
Omid Sadeghi, Maryam Fazel
Online Convex Optimization with Perturbed Constraints: Optimal Rates against Stronger Benchmarks
Victor Valls, George Iosifidis, Douglas Leith et al.
Online Learning Using Only Peer Prediction
Yang Liu, Dave Helmbold
Online Learning with Continuous Variations: Dynamic Regret and Reductions
Ching-An Cheng, Jonathan Lee, Ken Goldberg et al.
On Minimax Optimality of GANs for Robust Mean Estimation
Kaiwen Wu, Gavin Weiguang Ding, Ruitong Huang et al.
On Pruning for Score-Based Bayesian Network Structure Learning
Alvaro Henrique Chaim Correia, James Cussens, Cassio de Campos
On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis
Kohei Hayashi, Masaaki Imaizumi, Yuichi Yoshida
On the Completeness of Causal Discovery in the Presence of Latent Confounding with Tiered Background Knowledge
Bryan Andrews, Peter Spirtes, Gregory F. Cooper
On the Convergence of SARAH and Beyond
Bingcong Li, Meng Ma, Georgios B. Giannakis
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar
On the interplay between noise and curvature and its effect on optimization and generalization
Valentin Thomas, Fabian Pedregosa, Bart Merriënboer et al.
On the optimality of kernels for high-dimensional clustering
Leena C Vankadara, Debarghya Ghoshdastidar
On the Sample Complexity of Learning Sum-Product Networks
Ishaq Aden-Ali, Hassan Ashtiani
On Thompson Sampling for Smoother-than-Lipschitz Bandits
James Grant, David Leslie
Optimal Algorithms for Multiplayer Multi-Armed Bandits
PO-AN WANG, Alexandre Proutiere, Kaito Ariu et al.
Optimal Approximation of Doubly Stochastic Matrices
Nikitas Rontsis, Paul Goulart
Optimal Deterministic Coresets for Ridge Regression
Praneeth Kacham, David Woodruff
Optimal sampling in unbiased active learning
Henrik Imberg, Johan Jonasson, Marina Axelson-Fisk
Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning
Andrew Silva, Taylor Killian, Ivan Jimenez et al.
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning
Zhenzhang Ye, Thomas Möllenhoff, Tao Wu et al.