Learning to learn by gradient descent by gradient descent

14 June 2016

Marcin Andrychowicz

Misha Denil

Sergio Gomez Colmenarejo

Papers citing "Learning to learn by gradient descent by gradient descent"

44 / 394 papers shown

Title
Network Transplanting Quanshi Zhang Yu Yang Ying Nian Wu Song-Chun Zhu OOD 14 5 0 26 Apr 2018
Learning How to Self-Learn: Enhancing Self-Training Using Neural Reinforcement Learning Chenhua Chen Yue Zhang SSL 22 11 0 16 Apr 2018
Meta-Learning a Dynamical Language Model Thomas Wolf Julien Chaumond Clement Delangue 29 4 0 28 Mar 2018
Fast Parametric Learning with Activation Memorization Jack W. Rae Chris Dyer Peter Dayan Timothy Lillicrap KELM 41 46 0 27 Mar 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 69 1,411 0 24 Mar 2018
Neural Network Quine Oscar Chang Hod Lipson 18 23 0 15 Mar 2018
From Nodes to Networks: Evolving Recurrent Neural Networks Aditya Rawal Risto Miikkulainen 18 53 0 12 Mar 2018
Deep Learning in Mobile and Wireless Networking: A Survey Chaoyun Zhang P. Patras Hamed Haddadi 45 1,306 0 12 Mar 2018
On First-Order Meta-Learning Algorithms Alex Nichol Joshua Achiam John Schulman 67 2,217 0 08 Mar 2018
Evolved Policy Gradients Rein Houthooft Richard Y. Chen Phillip Isola Bradly C. Stadie Filip Wolski Jonathan Ho Pieter Abbeel 49 227 0 13 Feb 2018
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction Nataly Brukhim Amir Globerson 29 9 0 13 Feb 2018
Semi-Amortized Variational Autoencoders Yoon Kim Sam Wiseman Andrew C. Miller David Sontag Alexander M. Rush BDL DRL 33 243 0 07 Feb 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes Erin Grant Chelsea Finn Sergey Levine Trevor Darrell Thomas Griffiths BDL 26 505 0 26 Jan 2018
Rapid Adaptation with Conditionally Shifted Neurons Tsendsuren Munkhdalai Xingdi Yuan Soroush Mehri Adam Trischler 21 13 0 28 Dec 2017
A Bridge Between Hyperparameter Optimization and Learning-to-learn Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 35 20 0 18 Dec 2017
Building machines that adapt and compute like brains Brenden M. Lake J. Tenenbaum AI4CE FedML NAI AILaw 254 889 0 11 Nov 2017
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory Ron Amit Ron Meir BDL MLT 32 175 0 03 Nov 2017
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions Scott E. Reed Yutian Chen T. Paine Aaron van den Oord S. M. Ali Eslami Danilo Jimenez Rezende Oriol Vinyals Nando de Freitas 41 88 0 27 Oct 2017
A Survey of Model Compression and Acceleration for Deep Neural Networks Yu Cheng Duo Wang Pan Zhou Zhang Tao 40 1,087 0 23 Oct 2017
Neural Task Programming: Learning to Generalize Across Hierarchical Tasks Danfei Xu Suraj Nair Yuke Zhu J. Gao Animesh Garg Li Fei-Fei Silvio Savarese 25 193 0 04 Oct 2017
Neural Optimizer Search with Reinforcement Learning Irwan Bello Barret Zoph Vijay Vasudevan Quoc V. Le ODL 29 383 0 21 Sep 2017
Recurrent Inference Machines for Solving Inverse Problems P. Putzky Max Welling AI4CE 18 127 0 13 Jun 2017
Gradient Estimators for Implicit Models Yingzhen Li Richard Turner 35 104 0 19 May 2017
Metacontrol for Adaptive Imagination-Based Optimization Jessica B. Hamrick A. J. Ballard Razvan Pascanu Oriol Vinyals N. Heess Peter W. Battaglia 27 69 0 07 May 2017
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes Ahmed Alaa M. Schaar CML 33 298 0 10 Apr 2017
End-to-End Learning for Structured Prediction Energy Networks David Belanger Bishan Yang Andrew McCallum 14 136 0 16 Mar 2017
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 17 284 0 14 Mar 2017
Learning Gradient Descent: Better Generalization and Longer Horizons Kaifeng Lyu Shunhua Jiang Jian Li 20 113 0 10 Mar 2017
Learning to Optimize Neural Nets Ke Li Jitendra Malik 23 130 0 01 Mar 2017
Learning What Data to Learn Yang Fan Fei Tian Tao Qin Jiang Bian Tie-Yan Liu 13 79 0 28 Feb 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 104 1,503 0 25 Jan 2017
Learning to superoptimize programs - Workshop Version Rudy Bunel Alban Desmaison M. P. Kumar Philip Torr Pushmeet Kohli 27 10 0 04 Dec 2016
Two Methods For Wild Variational Inference Qiang Liu Yihao Feng BDL 32 19 0 30 Nov 2016
Diet Networks: Thin Parameters for Fat Genomics Adriana Romero P. Carrier Akram Erraqabi Tristan Sylvain Alex Auvolat Etienne Dejoie Marc-André Legault M. Dubé J. Hussin Yoshua Bengio 20 68 0 28 Nov 2016
Learning to Learn without Gradient Descent by Gradient Descent Yutian Chen Matthew W. Hoffman Sergio Gomez Colmenarejo Misha Denil Timothy Lillicrap Matt Botvinick Nando de Freitas 21 42 0 11 Nov 2016
RL $^2$ : Fast Reinforcement Learning via Slow Reinforcement Learning Yan Duan John Schulman Xi Chen Peter L. Bartlett Ilya Sutskever Pieter Abbeel OffRL 35 1,007 0 09 Nov 2016
Unrolled Generative Adversarial Networks Luke Metz Ben Poole David Pfau Jascha Narain Sohl-Dickstein GAN 59 1,001 0 07 Nov 2016
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning Dilin Wang Qiang Liu GAN BDL 38 118 0 06 Nov 2016
HyperNetworks David R Ha Andrew M. Dai Quoc V. Le 84 1,589 0 27 Sep 2016
Lie-X: Depth Image Based Articulated Object Pose Estimation, Tracking, and Action Recognition on Lie Groups Chi Xu L. Govindarajan Yu Zhang Li Cheng 24 109 0 13 Sep 2016
Deep Q-Networks for Accelerating the Training of Deep Neural Networks Jie Fu AI4CE 46 11 0 05 Jun 2016
Tradeoffs between Convergence Speed and Reconstruction Accuracy in Inverse Problems Raja Giryes Yonina C. Eldar A. Bronstein Guillermo Sapiro 17 85 0 30 May 2016
Stochastic modified equations and adaptive stochastic gradient algorithms Qianxiao Li Cheng Tai E. Weinan 30 279 0 19 Nov 2015
Probabilistic Line Searches for Stochastic Optimization Maren Mahsereci Philipp Hennig ODL 26 126 0 10 Feb 2015