Gradient-based Hyperparameter Optimization through Reversible Learning

11 February 2015

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

50 / 498 papers shown

Title
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 27 203 0 16 Nov 2019
Meta Label Correction for Noisy Label Learning Guoqing Zheng Ahmed Hassan Awadallah S. Dumais NoLa OffRL 27 178 0 10 Nov 2019
Penalty Method for Inversion-Free Deep Bilevel Optimization Akshay Mehra Jihun Hamm 24 46 0 08 Nov 2019
Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine Paul Vicol David Duvenaud DD 45 404 0 06 Nov 2019
A Simple Dynamic Learning Rate Tuning Algorithm For Automated Training of DNNs Koyel Mukherjee Alind Khare Ashish Verma 22 15 0 25 Oct 2019
MARTHE: Scheduling the Learning Rate Via Online Hypergradients Michele Donini Luca Franceschi Massimiliano Pontil Orchid Majumder P. Frasconi 25 7 0 18 Oct 2019
First-Order Preconditioning via Hypergradient Descent Theodore H. Moskovitz Rui Wang Janice Lan Sanyam Kapoor Thomas Miconi J. Yosinski Aditya Rawal AI4CE 31 8 0 18 Oct 2019
Meta-learning for fast classifier adaptation to new users of Signature Verification systems L. G. Hafemann R. Sabourin Luiz Eduardo Soares de Oliveira AAML 35 25 0 17 Oct 2019
Model-Agnostic Meta-Learning using Runge-Kutta Methods Daniel Jiwoong Im Yibo Jiang Nakul Verma 27 4 0 16 Oct 2019
Meta-Learning Deep Energy-Based Memory Models Sergey Bartunov Jack W. Rae Simon Osindero Timothy Lillicrap 45 34 0 07 Oct 2019
Generalized Inner Loop Meta-Learning Jaya Kumar Alageshan Brandon Amos A. Verma Phu Mon Htut Artem Molchanov Franziska Meier Douwe Kiela Kyunghyun Cho Soumith Chintala AI4CE 39 159 0 03 Oct 2019
Auto-Sizing the Transformer Network: Improving Speed, Efficiency, and Performance for Low-Resource Machine Translation Kenton W. Murray Jeffery Kinnison Toan Q. Nguyen Walter J. Scheirer David Chiang 17 21 0 01 Oct 2019
Gradient Descent: The Ultimate Optimizer Kartik Chandra Audrey Xie Jonathan Ragan-Kelley E. Meijer ODL 30 0 0 29 Sep 2019
Understanding and Robustifying Differentiable Architecture Search Arber Zela T. Elsken Tonmoy Saikia Yassine Marrakchi Thomas Brox Frank Hutter OOD AAML 66 369 0 20 Sep 2019
Regularized deep learning with nonconvex penalties Sujit Vettam Majnu John 19 5 0 11 Sep 2019
Meta-Learning with Implicit Gradients Aravind Rajeswaran Chelsea Finn Sham Kakade Sergey Levine 51 844 0 10 Sep 2019
A Baseline for Few-Shot Image Classification Guneet Singh Dhillon Pratik Chaudhari Avinash Ravichandran Stefano Soatto 36 575 0 06 Sep 2019
Meta Learning with Relational Information for Short Sequences Yujia Xie Haoming Jiang Feng Liu T. Zhao H. Zha 25 14 0 04 Sep 2019
Gradient Methods for Solving Stackelberg Games Roi Naveiro D. Insua 19 12 0 19 Aug 2019
On Defending Against Label Flipping Attacks on Malware Detection Systems R. Taheri R. Javidan Mohammad Shojafar Zahra Pooranian A. Miri Mauro Conti AAML 21 88 0 13 Aug 2019
AutoML: A Survey of the State-of-the-Art Xin He Kaiyong Zhao Xiaowen Chu 48 1,423 0 02 Aug 2019
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference Cuong C. Nguyen Thanh-Toan Do G. Carneiro OOD BDL UQCV 21 54 0 27 Jul 2019
Switchable Normalization for Learning-to-Normalize Deep Representation Ping Luo Ruimao Zhang Jiamin Ren Zhanglin Peng Jingyu Li 30 73 0 22 Jul 2019
Automated Machine Learning in Practice: State of the Art and Recent Results Lukas Tuggener Mohammadreza Amirian Katharina Rombach Stefan Lörwald Anastasia Varlet Christian Westermann Thilo Stadelmann 21 63 0 19 Jul 2019
Towards Understanding Generalization in Gradient-Based Meta-Learning Simon Guiroy Vikas Verma C. Pal 15 21 0 16 Jul 2019
Learning to Generate Synthetic 3D Training Data through Hybrid Gradient Dawei Yang Jia Deng 3DH 19 5 0 29 Jun 2019
MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data Lei Xu Shubhra (Santu) Karmaker K. Veeramachaneni AI4TS 16 4 0 28 Jun 2019
Data Cleansing for Models Trained with SGD Satoshi Hara Atsushi Nitanda Takanori Maehara TDI 34 68 0 20 Jun 2019
Meta-Learning via Learned Loss Sarah Bechtle Artem Molchanov Yevgen Chebotar Edward Grefenstette Ludovic Righetti Gaurav Sukhatme Franziska Meier 26 110 0 12 Jun 2019
Graduated Optimization of Black-Box Functions Weijia Shao C. Geißler F. Sivrikaya 28 2 0 04 Jun 2019
Learning to solve the credit assignment problem B. Lansdell P. Prakash Konrad Paul Kording 27 50 0 03 Jun 2019
Robustness of accelerated first-order algorithms for strongly convex optimization problems Hesameddin Mohammadi Meisam Razaviyayn M. Jovanović 17 41 0 27 May 2019
AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence Jeff Clune 17 116 0 27 May 2019
Neuro-Optimization: Learning Objective Functions Using Neural Networks Younghan Jeon Minsik Lee J. Choi 36 1 0 24 May 2019
Alpha MAML: Adaptive Model-Agnostic Meta-Learning Harkirat Singh Behl A. G. Baydin Philip Torr 33 67 0 17 May 2019
Online Hyper-parameter Learning for Auto-Augmentation Strategy Chen Lin Minghao Guo Chuming Li Yuan Xin Wei Wu Dahua Lin Wanli Ouyang Junjie Yan ODL 21 83 0 17 May 2019
Efficient Optimization of Loops and Limits with Randomized Telescoping Sums Alex Beatson Ryan P. Adams 17 21 0 16 May 2019
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment Chen Huang Shuangfei Zhai Walter A. Talbott Miguel Angel Bautista Shi Sun Carlos Guestrin J. Susskind 29 75 0 15 May 2019
Task-Driven Data Verification via Gradient Descent Siavash Golkar Kyunghyun Cho 14 0 0 14 May 2019
Data-Efficient Mutual Information Neural Estimator Xiaoyu Lin Indranil Sur Samuel A. Nastase Ajay Divakaran Uri Hasson Mohamed R. Amer DRL 11 20 0 08 May 2019
Differentiable Visual Computing Tzu-Mao Li 26 15 0 27 Apr 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 21 6 0 25 Apr 2019
Reducing The Search Space For Hyperparameter Optimization Using Group Sparsity Minsu Cho Chinmay Hegde 27 11 0 24 Apr 2019
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness Lan-Zhe Guo Yu-Feng Li Ming Li Jinfeng Yi Bowen Zhou Zhi-Hua Zhou 29 2 0 22 Apr 2019
Hierarchical Meta Learning Yingtian Zou Jiashi Feng 19 4 0 19 Apr 2019
An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning Yaoyao Liu Bernt Schiele Qianru Sun BDL 40 128 0 17 Apr 2019
Shakeout: A New Approach to Regularized Deep Neural Network Training Guoliang Kang Jun Yu Li Dacheng Tao 26 59 0 13 Apr 2019
Least Squares Auto-Tuning Shane T. Barratt Stephen P. Boyd MoMe 24 23 0 10 Apr 2019
Meta-Learning with Differentiable Convex Optimization Kwonjoon Lee Subhransu Maji Avinash Ravichandran Stefano Soatto 31 1,264 0 07 Apr 2019