Gradient-based Hyperparameter Optimization through Reversible Learning

11 February 2015

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

48 / 498 papers shown

Title
Stochastic Hyperparameter Optimization through Hypernetworks Jonathan Lorraine David Duvenaud 47 139 0 26 Feb 2018
SLAQ: Quality-Driven Scheduling for Distributed Machine Learning Haoyu Zhang Logan Stafman Andrew Or M. Freedman 38 140 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
Meta-Tracker: Fast and Robust Online Adaptation for Visual Object Trackers Eunbyung Park Alexander C. Berg VOT TTA 38 166 0 09 Jan 2018
A Bridge Between Hyperparameter Optimization and Learning-to-learn Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 35 20 0 18 Dec 2017
Nonparametric Neural Networks George Philipp J. Carbonell 27 21 0 14 Dec 2017
Extreme Dimension Reduction for Handling Covariate Shift Fulton Wang Cynthia Rudin 33 1 0 29 Nov 2017
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization Luis Muñoz-González Battista Biggio Ambra Demontis Andrea Paudice Vasin Wongrassamee Emil C. Lupu Fabio Roli AAML 29 626 0 29 Aug 2017
Image Augmentation using Radial Transform for Training Deep Neural Networks Hojjat Salehinejad S. Valaee T. Dowdell Joseph Barfett 21 11 0 14 Aug 2017
Analysis and Optimization of Convolutional Neural Network Architectures Martin Thoma 30 72 0 31 Jul 2017
Discretization-free Knowledge Gradient Methods for Bayesian Optimization Jian Wu P. Frazier BDL 21 9 0 20 Jul 2017
The Reversible Residual Network: Backpropagation Without Storing Activations Aidan Gomez Mengye Ren R. Urtasun Roger C. Grosse 39 543 0 14 Jul 2017
Kafnets: kernel-based non-parametric activation functions for neural networks Simone Scardapane S. Van Vaerenbergh Simone Totaro A. Uncini 22 12 0 13 Jul 2017
SHADHO: Massively Scalable Hardware-Aware Distributed Hyperparameter Optimization Jeffery Kinnison Nathaniel Kremer-Herman D. Thain Walter J. Scheirer 25 11 0 05 Jul 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 46 1,788 0 16 Jun 2017
Stochastic Training of Neural Networks via Successive Convex Approximations Simone Scardapane P. Di Lorenzo 24 9 0 15 Jun 2017
Hyperparameter Optimization: A Spectral Approach Elad Hazan Adam R. Klivans Yang Yuan 33 118 0 02 Jun 2017
Reinforcement Learning for Learning Rate Control Chang Xu Tao Qin G. Wang Tie-Yan Liu 24 34 0 31 May 2017
End-to-end representation learning for Correlation Filter based tracking Jack Valmadre Luca Bertinetto João F. Henriques Andrea Vedaldi Philip Torr 36 1,396 0 20 Apr 2017
Exploiting gradients and Hessians in Bayesian optimization and Bayesian quadrature Anqi Wu Mikio C. Aoi Jonathan W. Pillow 17 41 0 31 Mar 2017
Gradient-based Regularization Parameter Selection for Problems with Non-smooth Penalty Functions Jean Feng N. Simon 16 20 0 28 Mar 2017
End-to-End Learning for Structured Prediction Energy Networks David Belanger Bishan Yang Andrew McCallum 14 136 0 16 Mar 2017
Online Learning Rate Adaptation with Hypergradient Descent A. G. Baydin R. Cornish David Martínez-Rubio Mark Schmidt Frank Wood ODL 33 242 0 14 Mar 2017
Bayesian Optimization with Gradients Jian Wu Matthias Poloczek A. Wilson P. Frazier 29 210 0 13 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 508 11,727 0 09 Mar 2017
Forward and Reverse Gradient-Based Hyperparameter Optimization Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 133 409 0 06 Mar 2017
Meta Networks Tsendsuren Munkhdalai Hong-ye Yu GNN AI4CE 43 1,060 0 02 Mar 2017
Learning to Optimize Neural Nets Ke Li Jitendra Malik 23 130 0 01 Mar 2017
Variational Inference using Implicit Distributions Ferenc Huszár DRL GAN 22 135 0 27 Feb 2017
Structured Attention Networks Yoon Kim Carl Denton Luong Hoang Alexander M. Rush 47 461 0 03 Feb 2017
An Introduction to Deep Learning for the Physical Layer Tim O'Shea J. Hoydis AI4CE 89 2,177 0 02 Feb 2017
Tricks from Deep Learning A. G. Baydin Barak A. Pearlmutter J. Siskind ODL 16 9 0 10 Nov 2016
Unrolled Generative Adversarial Networks Luke Metz Ben Poole David Pfau Jascha Narain Sohl-Dickstein GAN 59 1,000 0 07 Nov 2016
Neural Network Architecture Optimization through Submodularity and Supermodularity Junqi Jin Ziang Yan Kun Fu Nan Jiang Changshui Zhang 24 11 0 01 Sep 2016
Optimizing Recurrent Neural Networks Architectures under Time Constraints Junqi Jin Ziang Yan Kun Fu Nan Jiang Changshui Zhang 24 2 0 29 Aug 2016
Learning to Optimize Ke Li Jitendra Malik 15 253 0 06 Jun 2016
Deep Q-Networks for Accelerating the Training of Deep Neural Networks Jie Fu AI4CE 46 11 0 05 Jun 2016
Asymptotically exact inference in differentiable generative models Matthew M. Graham Amos J. Storkey BDL 21 33 0 25 May 2016
Programming with a Differentiable Forth Interpreter Matko Bosnjak Tim Rocktaschel Jason Naradowsky Sebastian Riedel 17 148 0 21 May 2016
Hyperparameter optimization with approximate gradient Fabian Pedregosa 60 442 0 07 Feb 2016
DrMAD: Distilling Reverse-Mode Automatic Differentiation for Optimizing Hyperparameters of Deep Neural Networks Jie Fu Hongyin Luo Jiashi Feng K. H. Low Tat-Seng Chua 29 27 0 05 Jan 2016
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters Jelena Luketina Mathias Berglund Klaus Greff T. Raiko 29 173 0 20 Nov 2015
Structured Prediction Energy Networks David Belanger Andrew McCallum GNN 18 219 0 19 Nov 2015
Diversity Networks: Neural Network Compression Using Determinantal Point Processes Zelda E. Mariet S. Sra 30 129 0 16 Nov 2015
Speed learning on the fly Pierre-Yves Massé Yann Ollivier 29 13 0 08 Nov 2015
Early Stopping is Nonparametric Variational Inference D. Maclaurin David Duvenaud Ryan P. Adams BDL 38 95 0 06 Apr 2015
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 75 2,754 0 20 Feb 2015