Gradient-based Hyperparameter Optimization through Reversible Learning

11 February 2015

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

50 / 497 papers shown

Title
Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap Lingxi Xie Xin Chen Kaifeng Bi Longhui Wei Yuhui Xu ... Lanfei Wang Anxiang Xiao Jianlong Chang Xiaopeng Zhang Qi Tian ViT 43 108 0 04 Aug 2020
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice Li Yang Abdallah Shami AI4CE 20 2,032 0 30 Jul 2020
Stabilizing Bi-Level Hyperparameter Optimization using Moreau-Yosida Regularization Sauptik Dhar Unmesh Kurup Mohak Shah 32 2 0 27 Jul 2020
Regularized Flexible Activation Function Combinations for Deep Neural Networks Renlong Jie Junbin Gao A. Vasnev Minh-Ngoc Tran AI4CE 33 6 0 26 Jul 2020
CrossTransformers: spatially-aware few-shot transfer Carl Doersch Ankush Gupta Andrew Zisserman ViT 215 330 0 22 Jul 2020
A Gradient-based Bilevel Optimization Approach for Tuning Hyperparameters in Machine Learning Ankur Sinha Tanmay Khandait R. Mohanty 37 16 0 21 Jul 2020
Randomized Automatic Differentiation Deniz Oktay N. McGreivy Joshua Aduol Alex Beatson Ryan P. Adams ODL 22 26 0 20 Jul 2020
Gradient-based Hyperparameter Optimization Over Long Horizons P. Micaelli Amos Storkey 13 15 0 15 Jul 2020
Learning to Reweight with Deep Interactions Yang Fan Yingce Xia Lijun Wu Shufang Xie Weiqing Liu Jiang Bian Tao Qin Xiang-Yang Li 14 9 0 09 Jul 2020
Hyperparameter Optimization in Neural Networks via Structured Sparse Recovery Minsu Cho Mohammadreza Soltani C. Hegde 14 1 0 07 Jul 2020
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning Zhongzheng Ren Raymond A. Yeh A. Schwing 36 95 0 02 Jul 2020
Deep neural networks for the evaluation and design of photonic devices Jiaqi Jiang Ming-Keh Chen Jonathan A. Fan 27 393 0 30 Jun 2020
Guarantees for Tuning the Step Size using a Learning-to-Learn Approach Xiang Wang Shuai Yuan Chenwei Wu Rong Ge 18 16 0 30 Jun 2020
On the Iteration Complexity of Hypergradient Computation Riccardo Grazzi Luca Franceschi Massimiliano Pontil Saverio Salzo 48 193 0 29 Jun 2020
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding Bruno Lecouat Jean Ponce Julien Mairal AI4CE 8 6 0 26 Jun 2020
Learning Data Augmentation with Online Bilevel Optimization for Image Classification Saypraseuth Mounsaveng I. Laradji Ismail Ben Ayed David Vazquez M. Pedersoli 19 36 0 25 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Jackson Wang Roger C. Grosse J. Jacobsen 23 93 0 16 Jun 2020
A Multi-Phase Approach for Product Hierarchy Forecasting in Supply Chain Management: Application to MonarchFx Inc Sajjad Taghiyeh D. Lengacher Amir Hossein Sadeghi Amirreza Sahebifakhrabad R. Handfield AI4TS 28 15 0 16 Jun 2020
Learning Linear Programs from Optimal Decisions Yingcong Tan Daria Terekhov Andrew Delong 30 28 0 16 Jun 2020
Flexible Dataset Distillation: Learn Labels Instead of Images Ondrej Bohdal Yongxin Yang Timothy M. Hospedales DD 23 109 0 15 Jun 2020
Meta Approach to Data Augmentation Optimization Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 32 34 0 14 Jun 2020
Differentiable Neural Input Search for Recommender Systems Weiyu Cheng Yanyan Shen Linpeng Huang 23 36 0 08 Jun 2020
Multi-step Estimation for Gradient-based Meta-learning Jin-Hwa Kim Junyoung Park Yongseok Choi 22 1 0 08 Jun 2020
Learning Convex Optimization Models Akshay Agrawal Shane T. Barratt Stephen P. Boyd 29 40 0 07 Jun 2020
A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level Singleton Risheng Liu Pan Mu Xiaoming Yuan Shangzhi Zeng Jin Zhang 11 129 0 07 Jun 2020
AutoHAS: Efficient Hyperparameter and Architecture Search Xuanyi Dong Mingxing Tan Adams Wei Yu Daiyi Peng Bogdan Gabrys Quoc V. Le TPM 16 23 0 05 Jun 2020
UFO-BLO: Unbiased First-Order Bilevel Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller 32 7 0 05 Jun 2020
MetaInv-Net: Meta Inversion Network for Sparse View CT Image Reconstruction Haimiao Zhang Baodong Liu Hengyong Yu Bin Dong 24 61 0 30 May 2020
HyperSTAR: Task-Aware Hyperparameters for Deep Networks Gaurav Mittal Chang Liu Nikolaos Karianakis Victor Fragoso Mei Chen Y. Fu VLM 46 23 0 21 May 2020
Reducing catastrophic forgetting with learning on synthetic data Wojciech Masarczyk Ivona Tautkute DD 13 36 0 29 Apr 2020
A Comprehensive Overview and Survey of Recent Advances in Meta-Learning Huimin Peng VLM OffRL 14 35 0 17 Apr 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 76 1,935 0 11 Apr 2020
Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation Da Li Timothy M. Hospedales 22 102 0 09 Apr 2020
Online Hyperparameter Search Interleaved with Proximal Parameter Updates Luis Miguel Lopez Ramos B. Beferull-Lozano 13 3 0 06 Apr 2020
MetaPoison: Practical General-purpose Clean-label Data Poisoning Yifan Jiang Jonas Geiping Liam H. Fowl Gavin Taylor Tom Goldstein 16 188 0 01 Apr 2020
Rectified Meta-Learning from Noisy Labels for Robust Image-based Plant Disease Diagnosis Ruifeng Shi Deming Zhai Xianming Liu Junjun Jiang Wen Gao NoLa 6 7 0 17 Mar 2020
Regularisation Can Mitigate Poisoning Attacks: A Novel Analysis Based on Multiobjective Bilevel Optimisation Javier Carnerero-Cano Luis Muñoz-González P. Spencer Emil C. Lupu AAML 22 11 0 28 Feb 2020
A Self-Tuning Actor-Critic Algorithm Tom Zahavy Zhongwen Xu Vivek Veeriah Matteo Hessel Junhyuk Oh H. V. Hasselt David Silver Satinder Singh 25 13 0 28 Feb 2020
Learning to Continually Learn Shawn L. E. Beaulieu Lapo Frati Thomas Miconi Joel Lehman Kenneth O. Stanley Jeff Clune Nick Cheney KELM CLL 46 146 0 21 Feb 2020
Implicit differentiation of Lasso-type models for hyperparameter optimization Quentin Bertrand Quentin Klopfenstein Mathieu Blondel Samuel Vaiter Alexandre Gramfort Joseph Salmon 24 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
Regularized Evolutionary Population-Based Training J. Liang Santiago Gonzalez H. Shahrzad Risto Miikkulainen 14 9 0 11 Feb 2020
Super-efficiency of automatic differentiation for functions defined as a minimum Pierre Ablin Gabriel Peyré Thomas Moreau 12 42 0 10 Feb 2020
Can't Boil This Frog: Robustness of Online-Trained Autoencoder-Based Anomaly Detectors to Adversarial Poisoning Attacks Moshe Kravchik A. Shabtai AAML 14 1 0 07 Feb 2020
From Learning to Meta-Learning: Reduced Training Overhead and Complexity for Communication Systems Osvaldo Simeone Sangwoo Park Joonhyuk Kang AI4CE 31 62 0 05 Jan 2020
Robust Federated Learning Through Representation Matching and Adaptive Hyper-parameters Hesham Mostafa FedML 31 39 0 30 Dec 2019
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data F. Such Aditya Rawal Joel Lehman Kenneth O. Stanley Jeff Clune DD 19 154 0 17 Dec 2019
Memory-efficient Learning for Large-scale Computational Imaging -- NeurIPS deep inverse workshop Michael R. Kellman Jonathan I. Tamir E. Bostan Michael Lustig Laura Waller SupR 26 56 0 11 Dec 2019
Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search Xiangxiang Chu Tianbao Zhou Bo-Wen Zhang Jixiang Li 20 306 0 27 Nov 2019
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 20 203 0 16 Nov 2019