Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning

18 February 2020

Papers citing "Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning"

36 / 36 papers shown

Title
Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization Wei Jiang Sifan Yang Wenhao Yang Yibo Wang Yuanyu Wan Lijun Zhang 33 2 0 06 Jun 2024
On First-Order Meta-Reinforcement Learning with Moreau Envelopes Taha Toghani Sebastian Perez-Salazar César A. Uribe 29 2 0 20 May 2023
PersA-FL: Personalized Asynchronous Federated Learning Taha Toghani Soomin Lee César A. Uribe FedML 34 6 0 03 Oct 2022
Provable Generalization of Overparameterized Meta-learning Trained with SGD Yu Huang Yingbin Liang Longbo Huang MLT 26 8 0 18 Jun 2022
Will Bilevel Optimizers Benefit from Loops Kaiyi Ji Mingrui Liu Yingbin Liang Lei Ying 42 41 0 27 May 2022
A Fast and Convergent Proximal Algorithm for Regularized Nonconvex and Nonsmooth Bi-level Optimization Ziyi Chen B. Kailkhura Yi Zhou 26 8 0 30 Mar 2022
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning Haoxiang Wang Yite Wang Ruoyu Sun Bo-wen Li 29 27 0 17 Mar 2022
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization Wei Jiang Bokun Wang Yibo Wang Lijun Zhang Tianbao Yang 79 17 0 15 Feb 2022
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning Xidong Feng Bo Liu Jie Ren Luo Mai Rui Zhu Haifeng Zhang Jun Wang Yaodong Yang 14 12 0 31 Dec 2021
Biased Gradient Estimate with Drastic Variance Reduction for Meta Reinforcement Learning Yunhao Tang 6 7 0 14 Dec 2021
On the Convergence Theory for Hessian-Free Bilevel Algorithms Daouda Sow Kaiyi Ji Yingbin Liang 26 28 0 13 Oct 2021
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis Qi Chen Changjian Shui M. Marchand 40 43 0 29 Sep 2021
Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems Tianyi Chen Yuejiao Sun W. Yin 24 33 0 25 Jun 2021
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation Yunhao Tang Tadashi Kozuno Mark Rowland Rémi Munos Michal Valko OffRL 10 9 0 24 Jun 2021
Compositional federated learning: Applications in distributionally robust averaging and meta learning Feihu Huang Junyi Li FedML 22 15 0 21 Jun 2021
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation Haoxiang Wang Han Zhao Bo-wen Li 37 88 0 16 Jun 2021
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning Bokun Wang Zhuoning Yuan Yiming Ying Tianbao Yang FedML 56 9 0 09 Jun 2021
Provably Faster Algorithms for Bilevel Optimization Junjie Yang Kaiyi Ji Yingbin Liang 46 132 0 08 Jun 2021
Debiasing a First-order Heuristic for Approximate Bi-level Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller AI4CE 19 5 0 04 Jun 2021
Lower Bounds and Accelerated Algorithms for Bilevel Optimization Kaiyi Ji Yingbin Liang 18 57 0 07 Feb 2021
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks Alireza Fallah Aryan Mokhtari Asuman Ozdaglar 25 49 0 07 Feb 2021
Meta-learning with negative learning rates A. Bernacchia 17 17 0 01 Feb 2021
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond Risheng Liu Jiaxin Gao Jin Zhang Deyu Meng Zhouchen Lin AI4CE 56 222 0 27 Jan 2021
Inexact-ADMM Based Federated Meta-Learning for Fast and Continual Edge Learning Sheng Yue Ju Ren Jiang Xin Sen Lin Junshan Zhang FedML 27 44 0 16 Dec 2020
MetaGater: Fast Learning of Conditional Channel Gated Networks via Federated Meta-Learning Sen Lin Li Yang Zhezhi He Deliang Fan Junshan Zhang FedML AI4CE 17 5 0 25 Nov 2020
Bilevel Optimization: Convergence Analysis and Enhanced Design Kaiyi Ji Junjie Yang Yingbin Liang 28 245 0 15 Oct 2020
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning Giulia Denevi Massimiliano Pontil C. Ciliberto 34 39 0 25 Aug 2020
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization Tianyi Chen Yuejiao Sun W. Yin 48 81 0 25 Aug 2020
Global Convergence and Generalization Bound of Gradient-Based Meta-Learning with Deep Neural Nets Haoxiang Wang Ruoyu Sun Bo Li MLT AI4CE 16 14 0 25 Jun 2020
Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent Mehdi Abbana Bennani Thang Doan Masashi Sugiyama CLL 50 61 0 21 Jun 2020
Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters Kaiyi Ji J. Lee Yingbin Liang H. Vincent Poor 23 74 0 16 Jun 2020
Multi-step Estimation for Gradient-based Meta-learning Jin-Hwa Kim Junyoung Park Yongseok Choi 14 1 0 08 Jun 2020
UFO-BLO: Unbiased First-Order Bilevel Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller 32 7 0 05 Jun 2020
On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning Alireza Fallah Kristian Georgiev Aryan Mokhtari Asuman Ozdaglar 25 22 0 12 Feb 2020
Probabilistic Model-Agnostic Meta-Learning Chelsea Finn Kelvin Xu Sergey Levine BDL 176 666 0 07 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 341 11,684 0 09 Mar 2017