M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast
Self-Adaptation

M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation

28 February 2023

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Papers citing "M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation"

18 / 18 papers shown

Title
Symbolic Learning to Optimize: Towards Interpretability and Scalability Wenqing Zheng Tianlong Chen Ting-Kuei Hu Zhangyang Wang 115 19 0 13 Mar 2022
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies Paul Vicol Luke Metz Jascha Narain Sohl-Dickstein 91 68 0 27 Dec 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 243 236 0 23 Mar 2021
Training Stronger Baselines for Learning to Optimize Tianlong Chen Weiyi Zhang Jingyang Zhou Shiyu Chang Sijia Liu Lisa Amini Zhangyang Wang OffRL 81 51 0 18 Oct 2020
Bilevel Optimization: Convergence Analysis and Enhanced Design Kaiyi Ji Junjie Yang Yingbin Liang 199 261 0 15 Oct 2020
Automated Synthetic-to-Real Generalization Wuyang Chen Zhiding Yu Zhangyang Wang Anima Anandkumar 78 68 0 14 Jul 2020
Improved Adversarial Training via Learned Optimizer Yuanhao Xiong Cho-Jui Hsieh AAML 65 31 0 25 Apr 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 381 18,866 0 13 Feb 2020
Momentum Contrast for Unsupervised Visual Representation Learning Kaiming He Haoqi Fan Yuxin Wu Saining Xie Ross B. Girshick SSL 213 12,124 0 13 Nov 2019
Learning to Optimize in Swarms Yue Cao Tianlong Chen Zhangyang Wang Yang Shen 81 56 0 09 Nov 2019
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML Aniruddh Raghu M. Raghu Samy Bengio Oriol Vinyals 305 647 0 19 Sep 2019
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms Alireza Fallah Aryan Mokhtari Asuman Ozdaglar 88 225 0 27 Aug 2019
Hierarchically Structured Meta-learning Huaxiu Yao Ying Wei Junzhou Huang Z. Li 62 203 0 13 May 2019
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 233 1,276 0 04 Oct 2018
Learned Optimizers that Scale and Generalize Olga Wichrowska Niru Maheswaranathan Matthew W. Hoffman Sergio Gomez Colmenarejo Misha Denil Nando de Freitas Jascha Narain Sohl-Dickstein AI4CE 62 284 0 14 Mar 2017
Learning Gradient Descent: Better Generalization and Longer Horizons Kaifeng Lyu Shunhua Jiang Jian Li 79 114 0 10 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 829 11,943 0 09 Mar 2017
Learning to learn by gradient descent by gradient descent Marcin Andrychowicz Misha Denil Sergio Gomez Colmenarejo Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas 124 2,008 0 14 Jun 2016

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