Papers
4,122 papers found
Accelerating optimization over the space of probability measures
Shi Chen, Qin Li, Oliver Tse et al.
A Comparative Evaluation of Quantification Methods
Tobias Schumacher, Markus Strohmaier, Florian Lemmerich
Actor-Critic learning for mean-field control in continuous time
Noufel FRIKHA, Maximilien GERMAIN, Mathieu LAURIERE et al.
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
Boxin Zhao, Lingxiao Wang, Ziqi Liu et al.
Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos
Shao-Bo Lin, Xiaotong Liu, Di Wang et al.
A Decentralized Proximal Gradient Tracking Algorithm for Composite Optimization on Riemannian Manifolds
Lei Wang, Le Bao, Xin Liu
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization
Shouri Hu, Haowei Wang, Zhongxiang Dai et al.
A Hybrid Weighted Nearest Neighbour Classifier for Semi-Supervised Learning
Stephen M. S. Lee, Mehdi Soleymani
Algorithms for ridge estimation with convergence guarantees
Wanli Qiao, Wolfgang Polonik
Almost Sure Convergence of Dropout Algorithms for Neural Networks
Albert Senen--Cerda, Jaron Sanders
An Adaptive Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition
Qihang Lin, Negar Soheili, Runchao Ma et al.
An Asymptotically Optimal Coordinate Descent Algorithm for Learning Bayesian Networks from Gaussian Models
Tong Xu, Simge Küçükyavuz, Ali Shojaie et al.
An Augmentation Overlap Theory of Contrastive Learning
Qi Zhang, Yifei Wang, Yisen Wang
An Axiomatic Definition of Hierarchical Clustering
Ery Arias-Castro, Elizabeth Coda
A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization
Junwen Qiu, Xiao Li, Andre Milzarek
A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
Hugo Lebeau, Florent Chatelain, Romain Couillet
Are Ensembles Getting Better All the Time?
Pierre-Alexandre Mattei, Damien Garreau
Assumption-lean and data-adaptive post-prediction inference
Jiacheng Miao, Xinran Miao, Yixuan Wu et al.
A statistical perspective on algorithm unrolling models for inverse problems
Yves Atchade, Xinru Liu, Qiuyun Zhu
Asymptotic Inference for Multi-Stage Stationary Treatment Policy with Variable Selection
Daiqi Gao, Yufeng Liu, Donglin Zeng
A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs
Lukas Zierahn, Dirk van der Hoeven, Tal Lancewicki et al.
A Unified Framework to Enforce, Discover, and Promote Symmetry in Machine Learning
Samuel E. Otto, Nicholas Zolman, J. Nathan Kutz et al.
Autoencoders in Function Space
Justin Bunker, Mark Girolami, Hefin Lambley et al.
Backward Filtering Forward Guiding
Frank H. van der Meulen, S. Sommer