Gradient-based Hyperparameter Optimization through Reversible Learning

11 February 2015

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

50 / 497 papers shown

Title
Regularization Can Help Mitigate Poisoning Attacks... with the Right Hyperparameters Javier Carnerero-Cano Luis Muñoz-González P. Spencer Emil C. Lupu AAML 42 10 0 23 May 2021
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming Minkai Xu Wujie Wang Shitong Luo Chence Shi Yoshua Bengio Rafael Gómez-Bombarelli Jian Tang 3DV 37 78 0 15 May 2021
Bilevel Programs Meet Deep Learning: A Unifying View on Inference Learning Methods Christopher Zach FedML 16 5 0 15 May 2021
A hyperparameter-tuning approach to automated inverse planning Kelsey Maass Aleksandr Aravkin Minsun Kim 17 3 0 14 May 2021
Exploring the Similarity of Representations in Model-Agnostic Meta-Learning Thomas Goerttler Klaus Obermayer 13 4 0 12 May 2021
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification Haochen Liu Wei Jin Hamid Karimi Zitao Liu Jiliang Tang 8 30 0 06 May 2021
Implicit differentiation for fast hyperparameter selection in non-smooth convex learning Quentin Bertrand Quentin Klopfenstein Mathurin Massias Mathieu Blondel Samuel Vaiter Alexandre Gramfort Joseph Salmon 53 26 0 04 May 2021
Metadata Normalization Mandy Lu Qingyu Zhao Jiequan Zhang K. Pohl L. Fei-Fei Juan Carlos Niebles Ehsan Adeli 22 20 0 19 Apr 2021
Learning Normal Dynamics in Videos with Meta Prototype Network Hui Lv Chong Chen Zhen Cui Chunyan Xu Yong Li Jian Yang 30 139 0 14 Apr 2021
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach Simiao Zuo Chen Liang Haoming Jiang Xiaodong Liu Pengcheng He Jianfeng Gao Weizhu Chen T. Zhao 55 9 0 11 Apr 2021
Soft-Label Anonymous Gastric X-ray Image Distillation Guang Li Ren Togo Takahiro Ogawa Miki Haseyama DD 40 51 0 07 Apr 2021
Rethinking Graph Neural Architecture Search from Message-passing Shaofei Cai Liang Li Jincan Deng Beichen Zhang Zhengjun Zha Li Su Qingming Huang GNN AI4CE 19 53 0 26 Mar 2021
How to decay your learning rate Aitor Lewkowycz 41 24 0 23 Mar 2021
Robust MAML: Prioritization task buffer with adaptive learning process for model-agnostic meta-learning Thanh Nguyen Tung M. Luu T. Pham Sanzhar Rakhimkul Chang D. Yoo 22 10 0 15 Mar 2021
BODAME: Bilevel Optimization for Defense Against Model Extraction Y. Mori Atsushi Nitanda Akiko Takeda MIACV 32 4 0 11 Mar 2021
Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm Bin Gu Guodong Liu Yanfu Zhang Xiang Geng Heng-Chiao Huang 36 19 0 17 Feb 2021
Complex Momentum for Optimization in Games Jonathan Lorraine David Acuna Paul Vicol David Duvenaud 20 9 0 16 Feb 2021
A General Descent Aggregation Framework for Gradient-based Bi-level Optimization Risheng Liu Pan Mu Xiaoming Yuan Shangzhi Zeng Jin Zhang AI4CE 33 36 0 16 Feb 2021
Momentum Residual Neural Networks Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 27 57 0 15 Feb 2021
Lower Bounds and Accelerated Algorithms for Bilevel Optimization Kaiyi Ji Yingbin Liang 18 57 0 07 Feb 2021
HYDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks Yuanyuan Chen Boyang Albert Li Han Yu Pengcheng Wu Chunyan Miao TDI 24 39 0 04 Feb 2021
Synthetic Dataset Generation of Driver Telematics Banghee So J. Boucher Emiliano A. Valdez 25 24 0 30 Jan 2021
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond Risheng Liu Jiaxin Gao Jin Zhang Deyu Meng Zhouchen Lin AI4CE 59 222 0 27 Jan 2021
Optimizing Hyperparameters in CNNs using Bilevel Programming in Time Series Data Taniya Seth Pranab K. Muhuri 14 0 0 19 Jan 2021
On the Turnpike to Design of Deep Neural Nets: Explicit Depth Bounds T. Faulwasser Arne-Jens Hempel S. Streif 16 5 0 08 Jan 2021
HyperMorph: Amortized Hyperparameter Learning for Image Registration Andrew Hoopes Malte Hoffmann Bruce Fischl John Guttag Adrian V. Dalca 36 128 0 04 Jan 2021
Poisoning Attacks on Cyber Attack Detectors for Industrial Control Systems Moshe Kravchik Battista Biggio A. Shabtai AAML 19 28 0 23 Dec 2020
How Robust are Randomized Smoothing based Defenses to Data Poisoning? Akshay Mehra B. Kailkhura Pin-Yu Chen Jihun Hamm OOD AAML 17 32 0 02 Dec 2020
Scaling Down Deep Learning with MNIST-1D S. Greydanus Dmitry Kobak 13 20 0 29 Nov 2020
Long Short Term Memory Networks for Bandwidth Forecasting in Mobile Broadband Networks under Mobility Konstantinos Kousias A. Pappas Özgü Alay A. Argyriou Michael Riegler 9 1 0 20 Nov 2020
DeepRepair: Style-Guided Repairing for DNNs in the Real-world Operational Environment Bing Yu Hua Qi Qing Guo Felix Juefei Xu Xiaofei Xie L. Ma Jianjun Zhao 14 5 0 19 Nov 2020
Identification of state functions by physically-guided neural networks with physically-meaningful internal layers J. Ayensa-Jiménez M. H. Doweidar J. A. Sanz-Herrera Manuel Doblaré PINN 12 1 0 17 Nov 2020
Convergence Properties of Stochastic Hypergradients Riccardo Grazzi Massimiliano Pontil Saverio Salzo 22 26 0 13 Nov 2020
Teaching with Commentaries Aniruddh Raghu M. Raghu Simon Kornblith David Duvenaud Geoffrey E. Hinton 25 24 0 05 Nov 2020
Meta-learning Transferable Representations with a Single Target Domain Hong Liu Jeff Z. HaoChen Colin Wei Tengyu Ma AAML 43 5 0 03 Nov 2020
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 36 240 0 30 Oct 2020
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians Juhan Bae Roger C. Grosse 27 24 0 26 Oct 2020
AutoML to Date and Beyond: Challenges and Opportunities Shubhra (Santu) Karmaker Md. Mahadi Hassan Micah J. Smith Lei Xu Chengxiang Zhai K. Veeramachaneni 76 225 0 21 Oct 2020
Negotiating Team Formation Using Deep Reinforcement Learning Yoram Bachrach Richard Everett Edward Hughes Angeliki Lazaridou Joel Z Leibo Marc Lanctot Michael Bradley Johanson Wojciech M. Czarnecki T. Graepel 43 35 0 20 Oct 2020
New Properties of the Data Distillation Method When Working With Tabular Data Dmitry Medvedev A. Dýakonov DD 16 9 0 19 Oct 2020
Bilevel Optimization: Convergence Analysis and Enhanced Design Kaiyi Ji Junjie Yang Yingbin Liang 28 249 0 15 Oct 2020
Bi-level Score Matching for Learning Energy-based Latent Variable Models Fan Bao Chongxuan Li Kun Xu Hang Su Jun Zhu Bo Zhang 33 13 0 15 Oct 2020
Learning Optimal Representations with the Decodable Information Bottleneck Yann Dubois Douwe Kiela D. Schwab Ramakrishna Vedantam 26 43 0 27 Sep 2020
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves Luke Metz Niru Maheswaranathan C. Freeman Ben Poole Jascha Narain Sohl-Dickstein 33 62 0 23 Sep 2020
Smoke Testing for Machine Learning: Simple Tests to Discover Severe Defects Steffen Herbold Tobias Haar 9 10 0 03 Sep 2020
Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee Junyi Li Bin Gu Heng-Chiao Huang 18 41 0 01 Sep 2020
Adaptive Hierarchical Hyper-gradient Descent Renlong Jie Junbin Gao A. Vasnev Minh-Ngoc Tran 26 5 0 17 Aug 2020
AutoSimulate: (Quickly) Learning Synthetic Data Generation Harkirat Singh Behl A. G. Baydin Ran Gal Philip Torr Vibhav Vineet 16 23 0 16 Aug 2020
Efficient hyperparameter optimization by way of PAC-Bayes bound minimization John J. Cherian Andrew G. Taube R. McGibbon Panagiotis Angelikopoulos Guy Blanc M. Snarski D. D. Richman J. L. Klepeis D. Shaw 12 6 0 14 Aug 2020
Network Architecture Search for Domain Adaptation Yichen Li Xingchao Peng OOD 21 15 0 13 Aug 2020