Incremental Learning-to-Learn with Statistical Guarantees

Incremental Learning-to-Learn with Statistical Guarantees

21 March 2018

Dimitris Stamos

Massimiliano Pontil

Papers citing "Incremental Learning-to-Learn with Statistical Guarantees"

17 / 17 papers shown

Title
Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy Chen Wang Kaiyi Ji Junyi Geng Zhongqiang Ren Taimeng Fu ... Yi Du Qihang Li Y. Yang Xiao Lin Zhipeng Zhao SSL 83 9 0 28 Jan 2025
An Information-Theoretic Analysis of In-Context Learning Hong Jun Jeon Jason D. Lee Qi Lei Benjamin Van Roy 27 18 0 28 Jan 2024
Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes Charles Riou Pierre Alquier Badr-Eddine Chérief-Abdellatif 40 8 0 23 Feb 2023
Meta Representation Learning with Contextual Linear Bandits Leonardo Cella Karim Lounici Massimiliano Pontil 34 5 0 30 May 2022
Nearly Minimax Algorithms for Linear Bandits with Shared Representation Jiaqi Yang Qi Lei Jason D. Lee S. Du 35 16 0 29 Mar 2022
Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms Javad Azizi T. Duong Yasin Abbasi-Yadkori András Gyorgy Claire Vernade Mohammad Ghavamzadeh 28 8 0 25 Feb 2022
On the Power of Multitask Representation Learning in Linear MDP Rui Lu Gao Huang S. Du 24 28 0 15 Jun 2021
Improving Few-Shot Learning through Multi-task Representation Learning Theory Quentin Bouniot I. Redko Romaric Audigier Angélique Loesch Amaury Habrard 45 10 0 05 Oct 2020
Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent Mehdi Abbana Bennani Thang Doan Masashi Sugiyama CLL 50 61 0 21 Jun 2020
Meta-learning with Stochastic Linear Bandits Leonardo Cella A. Lazaric Massimiliano Pontil FedML 22 56 0 18 May 2020
Provable Representation Learning for Imitation Learning via Bi-level Optimization Sanjeev Arora S. Du Sham Kakade Yuping Luo Nikunj Saunshi 18 60 0 24 Feb 2020
Adaptive Gradient-Based Meta-Learning Methods M. Khodak Maria-Florina Balcan Ameet Talwalkar FedML 16 353 0 06 Jun 2019
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization Giulia Denevi C. Ciliberto Riccardo Grazzi Massimiliano Pontil 20 108 0 25 Mar 2019
Provable Guarantees for Gradient-Based Meta-Learning M. Khodak Maria-Florina Balcan Ameet Talwalkar FedML 22 147 0 27 Feb 2019
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 110 716 0 13 Jun 2018
New Perspectives on k-Support and Cluster Norms Andrew M. McDonald Massimiliano Pontil Dimitris Stamos 61 58 0 06 Mar 2014
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 101 570 0 08 Dec 2012