Hyperparameter optimization with approximate gradient

7 February 2016

Papers citing "Hyperparameter optimization with approximate gradient"

47 / 247 papers shown

Title
A Self-Tuning Actor-Critic Algorithm Tom Zahavy Zhongwen Xu Vivek Veeriah Matteo Hessel Junhyuk Oh H. V. Hasselt David Silver Satinder Singh 18 13 0 28 Feb 2020
Implicit differentiation of Lasso-type models for hyperparameter optimization Quentin Bertrand Quentin Klopfenstein Mathieu Blondel Samuel Vaiter Alexandre Gramfort Joseph Salmon 22 64 0 20 Feb 2020
Learning Adaptive Loss for Robust Learning with Noisy Labels Jun Shu Qian Zhao Keyu Chen Zongben Xu Deyu Meng NoLa OOD 19 23 0 16 Feb 2020
PHOTONAI -- A Python API for Rapid Machine Learning Model Development Ramona Leenings N. Winter Lucas Plagwitz V. Holstein J. Ernsting ... N. Opel Benjamin Risse Xiaoyi Jiang U. Dannlowski Tim Hahn LM&MA 37 28 0 13 Feb 2020
Super-efficiency of automatic differentiation for functions defined as a minimum Pierre Ablin Gabriel Peyré Thomas Moreau 4 42 0 10 Feb 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 74 6,079 0 10 Dec 2019
Meta Label Correction for Noisy Label Learning Guoqing Zheng Ahmed Hassan Awadallah S. Dumais NoLa OffRL 24 178 0 10 Nov 2019
Penalty Method for Inversion-Free Deep Bilevel Optimization Akshay Mehra Jihun Hamm 24 45 0 08 Nov 2019
Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine Paul Vicol David Duvenaud DD 27 402 0 06 Nov 2019
AReN: Assured ReLU NN Architecture for Model Predictive Control of LTI Systems James Ferlez Yasser Shoukry 9 17 0 05 Nov 2019
MARTHE: Scheduling the Learning Rate Via Online Hypergradients Michele Donini Luca Franceschi Massimiliano Pontil Orchid Majumder P. Frasconi 17 7 0 18 Oct 2019
Gradient Descent: The Ultimate Optimizer Kartik Chandra Audrey Xie Jonathan Ragan-Kelley E. Meijer ODL 20 0 0 29 Sep 2019
The Differentiable Cross-Entropy Method Brandon Amos Denis Yarats 29 54 0 27 Sep 2019
Understanding and Robustifying Differentiable Architecture Search Arber Zela T. Elsken Tonmoy Saikia Yassine Marrakchi Thomas Brox Frank Hutter OOD AAML 66 366 0 20 Sep 2019
Modular Meta-Learning with Shrinkage Yutian Chen A. Friesen Feryal M. P. Behbahani Arnaud Doucet David Budden Matthew W. Hoffman Nando de Freitas KELM OffRL 23 35 0 12 Sep 2019
Meta-Learning with Implicit Gradients Aravind Rajeswaran Chelsea Finn Sham Kakade Sergey Levine 19 844 0 10 Sep 2019
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Zhijun Mai Guosheng Hu Dexiong Chen Fumin Shen Heng Tao Shen 22 41 0 27 Aug 2019
AutoML: A Survey of the State-of-the-Art Xin He Kaiyong Zhao X. Chu 20 1,420 0 02 Aug 2019
Learning Effective Loss Functions Efficiently Matthew J. Streeter 6 8 0 28 Jun 2019
Graduated Optimization of Black-Box Functions Weijia Shao C. Geißler F. Sivrikaya 11 2 0 04 Jun 2019
Benchmark and Survey of Automated Machine Learning Frameworks Marc-André Zöller Marco F. Huber 25 86 0 26 Apr 2019
Forecasting in Big Data Environments: an Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet) Ali Habibnia E. Maasoumi 18 5 0 25 Apr 2019
Least Squares Auto-Tuning Shane T. Barratt Stephen P. Boyd MoMe 19 23 0 10 Apr 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
Learning Optimal Linear Regularizers Matthew J. Streeter 6 8 0 19 Feb 2019
Fast Efficient Hyperparameter Tuning for Policy Gradients Supratik Paul Vitaly Kurin Shimon Whiteson 22 32 0 18 Feb 2019
Parallel Contextual Bandits in Wireless Handover Optimization Igor Colin Albert Thomas M. Draief 18 5 0 21 Jan 2019
Dataset Distillation Tongzhou Wang Jun-Yan Zhu Antonio Torralba Alexei A. Efros DD 11 291 0 27 Nov 2018
Using Known Information to Accelerate HyperParameters Optimization Based on SMBO Daning Cheng Hanping Zhang Xia Fen Shigang Li Yunquan Zhang 14 0 0 08 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 9 6 0 01 Nov 2018
Automated Machine Learning: From Principles to Practices Quanming Yao Mengshuo Wang Hugo Jair Escalante Huan Zhao Qiang Yang 22 257 0 31 Oct 2018
Truncated Back-propagation for Bilevel Optimization Amirreza Shaban Ching-An Cheng Nathan Hatch Byron Boots 36 262 0 25 Oct 2018
Safe Grid Search with Optimal Complexity Eugène Ndiaye Tam Le Olivier Fercoq Joseph Salmon Ichiro Takeuchi 35 45 0 12 Oct 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
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance Giulia Luise Alessandro Rudi Massimiliano Pontil C. Ciliberto OT 24 130 0 30 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
Optimizing for Generalization in Machine Learning with Cross-Validation Gradients Shane T. Barratt Rishi Sharma 14 7 0 18 May 2018
MLtuner: System Support for Automatic Machine Learning Tuning Henggang Cui G. Ganger Phillip B. Gibbons 14 6 0 20 Mar 2018
Stochastic Hyperparameter Optimization through Hypernetworks Jonathan Lorraine David Duvenaud 41 139 0 26 Feb 2018
A Bridge Between Hyperparameter Optimization and Learning-to-learn Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 35 20 0 18 Dec 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 13 624 0 29 Aug 2017
Discretization-free Knowledge Gradient Methods for Bayesian Optimization Jian Wu P. Frazier BDL 13 9 0 20 Jul 2017
Bayesian Optimization with Gradients Jian Wu Matthias Poloczek A. Wilson P. Frazier 21 209 0 13 Mar 2017
Forward and Reverse Gradient-Based Hyperparameter Optimization Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 133 409 0 06 Mar 2017