Gradient-based Hyperparameter Optimization through Reversible Learning

11 February 2015

Papers citing "Gradient-based Hyperparameter Optimization through Reversible Learning"

50 / 497 papers shown

Title
Learning Discrete Structures for Graph Neural Networks Luca Franceschi Mathias Niepert Massimiliano Pontil X. He GNN 24 410 0 28 Mar 2019
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions M. Mackay Paul Vicol Jonathan Lorraine David Duvenaud Roger C. Grosse 27 164 0 07 Mar 2019
Quantifying contribution and propagation of error from computational steps, algorithms and hyperparameter choices in image classification pipelines Aritra Chowdhury M. Magdon-Ismail B. Yener 30 0 0 21 Feb 2019
Random Search and Reproducibility for Neural Architecture Search Liam Li Ameet Talwalkar OOD 33 717 0 20 Feb 2019
Learning to Generalize from Sparse and Underspecified Rewards Rishabh Agarwal Chen Liang Dale Schuurmans Mohammad Norouzi OffRL 49 97 0 19 Feb 2019
Meta-Curvature Eunbyung Park Junier B. Oliva BDL 18 122 0 09 Feb 2019
Hyper-parameter Tuning under a Budget Constraint Zhiyun Lu Chao-Kai Chiang Fei Sha 9 17 0 01 Feb 2019
Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems D. Mguni Joel Jennings Sergio Valcarcel Macua Emilio Sison S. Ceppi Enrique Munoz de Cote 8 39 0 30 Jan 2019
BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees Yongjoo Park Jingyi Qing Xiaoyang Shen Barzan Mozafari VLM 8 27 0 26 Dec 2018
Deep Inverse Optimization Yingcong Tan Andrew Delong Daria Terekhov 14 22 0 03 Dec 2018
Deep Learning Application in Security and Privacy -- Theory and Practice: A Position Paper Julia A. Meister Raja Naeem Akram K. Markantonakis 16 0 0 01 Dec 2018
Dataset Distillation Tongzhou Wang Jun-Yan Zhu Antonio Torralba Alexei A. Efros DD 13 291 0 27 Nov 2018
Do Normalization Layers in a Deep ConvNet Really Need to Be Distinct? Ping Luo Zhanglin Peng Jiamin Ren Ruimao Zhang FAtt OOD 6 7 0 19 Nov 2018
A Batched Scalable Multi-Objective Bayesian Optimization Algorithm Xi Lin Hui-Ling Zhen Zhenhua Li Qingfu Zhang Sam Kwong 6 11 0 04 Nov 2018
Efficient Online Hyperparameter Optimization for Kernel Ridge Regression with Applications to Traffic Time Series Prediction Hongyuan Zhan G. Gomes Xin Li Kamesh Madduri Kesheng Wu 11 6 0 01 Nov 2018
Towards learning-to-learn B. Lansdell Konrad Paul Kording 23 19 0 01 Nov 2018
Learning to Teach with Dynamic Loss Functions Lijun Wu Fei Tian Yingce Xia Yang Fan Tao Qin Jianhuang Lai Tie-Yan Liu 19 111 0 29 Oct 2018
Reversible Recurrent Neural Networks M. Mackay Paul Vicol Jimmy Ba Roger C. Grosse 6 52 0 25 Oct 2018
Truncated Back-propagation for Bilevel Optimization Amirreza Shaban Ching-An Cheng Nathan Hatch Byron Boots 36 262 0 25 Oct 2018
Understanding and correcting pathologies in the training of learned optimizers Luke Metz Niru Maheswaranathan Jeremy Nixon C. Freeman Jascha Narain Sohl-Dickstein ODL 25 149 0 24 Oct 2018
AutoLoss: Learning Discrete Schedules for Alternate Optimization Haowen Xu Huan Zhang Zhiting Hu Xiaodan Liang Ruslan Salakhutdinov Eric P. Xing 26 30 0 04 Oct 2018
Learning with Random Learning Rates Léonard Blier Pierre Wolinski Yann Ollivier OOD 18 20 0 02 Oct 2018
Interactive Agent Modeling by Learning to Probe Tianmin Shu Caiming Xiong Ying Nian Wu Song-Chun Zhu LM&Ro 16 2 0 01 Oct 2018
M $^3$ RL: Mind-aware Multi-agent Management Reinforcement Learning Tianmin Shu Yuandong Tian 20 53 0 29 Sep 2018
Deep Bilevel Learning Simon Jenni Paolo Favaro NoLa 11 114 0 05 Sep 2018
TherML: Thermodynamics of Machine Learning Alexander A. Alemi Ian S. Fischer DRL AI4CE 24 27 0 11 Jul 2018
Trust-Region Algorithms for Training Responses: Machine Learning Methods Using Indefinite Hessian Approximations Jennifer B. Erway J. Griffin Roummel F. Marcia Riadh Omheni 8 24 0 01 Jul 2018
Guided evolutionary strategies: Augmenting random search with surrogate gradients Niru Maheswaranathan Luke Metz George Tucker Dami Choi Jascha Narain Sohl-Dickstein 22 20 0 26 Jun 2018
Attention-based Few-Shot Person Re-identification Using Meta Learning Alireza Rahimpour Hairong Qi 19 5 0 24 Jun 2018
DARTS: Differentiable Architecture Search Hanxiao Liu Karen Simonyan Yiming Yang 82 4,301 0 24 Jun 2018
Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning Luca Franceschi Riccardo Grazzi Massimiliano Pontil Saverio Salzo P. Frasconi 17 2 0 13 Jun 2018
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 110 717 0 13 Jun 2018
Learning in Integer Latent Variable Models with Nested Automatic Differentiation Daniel Sheldon Kevin Winner Debora Sujono 15 3 0 08 Jun 2018
Parallel Architecture and Hyperparameter Search via Successive Halving and Classification Manoj Kumar George E. Dahl Vijay Vasudevan Mohammad Norouzi 20 25 0 25 May 2018
Meta-Gradient Reinforcement Learning Zhongwen Xu H. V. Hasselt David Silver 38 324 0 24 May 2018
Neural Generative Models for Global Optimization with Gradients Louis Faury Flavian Vasile Clément Calauzènes Olivier Fercoq 6 2 0 22 May 2018
Meta-learning with differentiable closed-form solvers Luca Bertinetto João F. Henriques Philip Torr Andrea Vedaldi ODL 30 920 0 21 May 2018
Optimizing for Generalization in Machine Learning with Cross-Validation Gradients Shane T. Barratt Rishi Sharma 14 7 0 18 May 2018
Regularization Learning Networks: Deep Learning for Tabular Datasets Ira Shavitt E. Segal AI4CE 26 20 0 16 May 2018
Towards Autonomous Reinforcement Learning: Automatic Setting of Hyper-parameters using Bayesian Optimization Juan Cruz Barsce J. Palombarini E. Martínez GP 16 33 0 12 May 2018
Holarchic Structures for Decentralized Deep Learning - A Performance Analysis Evangelos Pournaras S. Yadhunathan A. Diaconescu 6 13 0 07 May 2018
Reinforced Co-Training Jiawei Wu Lei Li William Yang Wang OffRL 22 51 0 17 Apr 2018
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization Peter L. Bartlett S. Evans Philip M. Long 73 31 0 13 Apr 2018
Meta-Learning Update Rules for Unsupervised Representation Learning Luke Metz Niru Maheswaranathan Brian Cheung Jascha Narain Sohl-Dickstein SSL OOD 22 121 0 31 Mar 2018
MLtuner: System Support for Automatic Machine Learning Tuning Henggang Cui G. Ganger Phillip B. Gibbons 14 6 0 20 Mar 2018
Reviving and Improving Recurrent Back-Propagation Renjie Liao Yuwen Xiong Ethan Fetaya Lisa Zhang Kijung Yoon Xaq Pitkow R. Urtasun R. Zemel BDL 38 118 0 16 Mar 2018
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing---and Back Elliot Meyerson Risto Miikkulainen 25 45 0 11 Mar 2018
Evolutionary Architecture Search For Deep Multitask Networks J. Liang Elliot Meyerson Risto Miikkulainen 39 120 0 10 Mar 2018
Understanding Short-Horizon Bias in Stochastic Meta-Optimization Yuhuai Wu Mengye Ren Renjie Liao Roger C. Grosse 22 138 0 06 Mar 2018
Stochastic Hyperparameter Optimization through Hypernetworks Jonathan Lorraine David Duvenaud 41 139 0 26 Feb 2018