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Provable Lifelong Learning of Representations

Provable Lifelong Learning of Representations

27 October 2021
Xinyuan Cao
Weiyang Liu
Santosh Vempala
    CLL
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Papers citing "Provable Lifelong Learning of Representations"

11 / 11 papers shown
Title
Action Flow Matching for Continual Robot Learning
Action Flow Matching for Continual Robot Learning
Alejandro Murillo-Gonzalez
Lantao Liu
CLL
32
0
0
25 Apr 2025
A Statistical Theory of Regularization-Based Continual Learning
A Statistical Theory of Regularization-Based Continual Learning
Xuyang Zhao
Huiyuan Wang
Weiran Huang
Wei Lin
19
12
0
10 Jun 2024
Last Iterate Convergence of Incremental Methods and Applications in
  Continual Learning
Last Iterate Convergence of Incremental Methods and Applications in Continual Learning
Xu Cai
Jelena Diakonikolas
23
5
0
11 Mar 2024
The Ideal Continual Learner: An Agent That Never Forgets
The Ideal Continual Learner: An Agent That Never Forgets
Liangzu Peng
Paris V. Giampouras
René Vidal
CLL
106
26
0
29 Apr 2023
Theory on Forgetting and Generalization of Continual Learning
Theory on Forgetting and Generalization of Continual Learning
Sen Lin
Peizhong Ju
Yitao Liang
Ness B. Shroff
CLL
21
40
0
12 Feb 2023
Continual Learning by Modeling Intra-Class Variation
Continual Learning by Modeling Intra-Class Variation
L. Yu
Tianyang Hu
Lanqing Hong
Zhen Liu
Adrian Weller
Weiyang Liu
CLL
30
11
0
11 Oct 2022
Memory Bounds for Continual Learning
Memory Bounds for Continual Learning
Xi Chen
Christos H. Papadimitriou
Binghui Peng
CLL
LRM
12
20
0
22 Apr 2022
Nearly Minimax Algorithms for Linear Bandits with Shared Representation
Nearly Minimax Algorithms for Linear Bandits with Shared Representation
Jiaqi Yang
Qi Lei
Jason D. Lee
S. Du
16
13
0
29 Mar 2022
Continual learning: a feature extraction formalization, an efficient
  algorithm, and fundamental obstructions
Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions
Binghui Peng
Andrej Risteski
CLL
OOD
12
10
0
27 Mar 2022
The Advantage of Conditional Meta-Learning for Biased Regularization and
  Fine-Tuning
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning
Giulia Denevi
Massimiliano Pontil
C. Ciliberto
29
35
0
25 Aug 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
237
11,568
0
09 Mar 2017
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