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The Generalization Ability of Online Algorithms for Dependent Data

11 October 2011

Papers citing "The Generalization Ability of Online Algorithms for Dependent Data"

26 / 26 papers shown

Title
Statistical Inference with Stochastic Gradient Methods under $φ$ -mixing Data Ruiqi Liu Xinyu Chen Zuofeng Shang FedML 82 6 0 24 Feb 2023
Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data Abhishek Roy Krishnakumar Balasubramanian Saeed Ghadimi 66 9 0 22 Jun 2022
Learning with little mixing Ingvar M. Ziemann Stephen Tu 113 30 0 16 Jun 2022
Learning from time-dependent streaming data with online stochastic algorithms Antoine Godichon-Baggioni Nicklas Werge Olivier Wintenberger 99 3 0 25 May 2022
Benign Overfitting in Time Series Linear Models with Over-Parameterization Shogo H. Nakakita Masaaki Imaizumi AI4TS 285 5 0 18 Apr 2022
Single Trajectory Nonparametric Learning of Nonlinear Dynamics Ingvar M. Ziemann H. Sandberg Nikolai Matni 71 25 0 16 Feb 2022
Risk Adversarial Learning System for Connected and Autonomous Vehicle Charging M. S. Munir Ki Tae Kim K. Thar Dusit Niyato Choong Seon Hong 23 5 0 02 Aug 2021
Exponential Weights Algorithms for Selective Learning Mingda Qiao Gregory Valiant 37 2 0 29 Jun 2021
Three rates of convergence or separation via U-statistics in a dependent framework Quentin Duchemin Yohann De Castro C. Lacour 26 0 0 24 Jun 2021
Stochastic Online Convex Optimization. Application to probabilistic time series forecasting Olivier Wintenberger AI4TS 89 8 0 01 Feb 2021
Multi-Agent Meta-Reinforcement Learning for Self-Powered and Sustainable Edge Computing Systems M. S. Munir N. H. Tran Walid Saad Choong Seon Hong 140 20 0 20 Feb 2020
Learning from weakly dependent data under Dobrushin's condition Y. Dagan C. Daskalakis Nishanth Dikkala S. Jayanti 89 24 0 21 Jun 2019
Regression from Dependent Observations C. Daskalakis Nishanth Dikkala Ioannis Panageas 87 30 0 08 May 2019
Sample Splitting and Weak Assumption Inference For Time Series Robert Lunde 48 2 0 20 Feb 2019
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme Belhal Karimi B. Miasojedow Eric Moulines Hoi-To Wai 97 91 0 02 Feb 2019
A Primer on PAC-Bayesian Learning Benjamin Guedj 171 223 0 16 Jan 2019
Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator Stephen Tu Benjamin Recht OffRL 78 131 0 22 Dec 2017
Empirical risk minimization and complexity of dynamical models K. Mcgoff A. Nobel 46 11 0 18 Nov 2016
Simpler PAC-Bayesian Bounds for Hostile Data Pierre Alquier Benjamin Guedj 161 72 0 23 Oct 2016
Statistical Learning under Nonstationary Mixing Processes Steve Hanneke Liu Yang 43 11 0 26 Dec 2015
Conditional Risk Minimization for Stochastic Processes Alexander Zimin Christoph H. Lampert 100 7 0 09 Oct 2015
Optimal learning with Bernstein Online Aggregation Olivier Wintenberger FedML 160 79 0 04 Apr 2014
Online Learning with Pairwise Loss Functions Bernie Wang Roni Khardon Dmitry Pechyony R. Jones 128 10 0 22 Jan 2013
Nonparametric risk bounds for time-series forecasting D. McDonald C. Shalizi M. Schervish AI4TS 141 28 0 03 Dec 2012
The Interplay Between Stability and Regret in Online Learning Ankan Saha Prateek Jain Ambuj Tewari 85 15 0 26 Nov 2012
Prediction of time series by statistical learning: general losses and fast rates Pierre Alquier Xiaoyin Li Olivier Wintenberger AI4TS 172 47 0 08 Nov 2012