Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization

21 March 2016

Papers citing "Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization"

50 / 262 papers shown

Title
AutoBERT-Zero: Evolving BERT Backbone from Scratch Jiahui Gao Hang Xu Han Shi Xiaozhe Ren Philip L. H. Yu Xiaodan Liang Xin Jiang Zhenguo Li 21 37 0 15 Jul 2021
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges B. Bischl Martin Binder Michel Lang Tobias Pielok Jakob Richter ... Theresa Ullmann Marc Becker A. Boulesteix Difan Deng Marius Lindauer 85 448 0 13 Jul 2021
Remote Blood Oxygen Estimation From Videos Using Neural Networks J. Mathew Xin Tian Min Wu Chau-Wai Wong 31 37 0 11 Jul 2021
SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar Michael Laskey Kevin Stone Brijen Thananjeyan Mark Tjersland 48 25 0 30 Jun 2021
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits Wenshuo Guo Kumar Krishna Agrawal Aditya Grover Vidya Muthukumar A. Pananjady 16 8 0 28 Jun 2021
Multi-objective Asynchronous Successive Halving Robin Schmucker Michele Donini Muhammad Bilal Zafar David Salinas Cédric Archambeau 32 23 0 23 Jun 2021
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better Gaurav Menghani VLM MedIm 23 366 0 16 Jun 2021
HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML Sebastian Pineda Arango H. Jomaa Martin Wistuba Josif Grabocka 24 55 0 11 Jun 2021
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization E. Lee David Eriksson Valerio Perrone Matthias Seeger 35 22 0 10 Jun 2021
A multi-objective perspective on jointly tuning hardware and hyperparameters David Salinas Valerio Perrone Olivier Cruchant Cédric Archambeau 32 13 0 10 Jun 2021
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing M. Khodak Renbo Tu Tian Li Liam Li Maria-Florina Balcan Virginia Smith Ameet Talwalkar FedML 43 78 0 08 Jun 2021
JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data Kourosh Hakhamaneshi Pieter Abbeel Vladimir M. Stojanović Aditya Grover 27 10 0 02 Jun 2021
A hyperparameter-tuning approach to automated inverse planning Kelsey Maass Aleksandr Aravkin Minsun Kim 19 3 0 14 May 2021
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization Julia Guerrero-Viu Sven Hauns Sergio Izquierdo Guilherme Miotto Simon Schrodi André Biedenkapp T. Elsken Difan Deng Marius Lindauer Frank Hutter AI4CE 17 25 0 03 May 2021
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020 Ryan Turner David Eriksson M. McCourt J. Kiili Eero Laaksonen Zhen Xu Isabelle M Guyon BDL 30 289 0 20 Apr 2021
Rethinking Neural Operations for Diverse Tasks Nicholas Roberts M. Khodak Tri Dao Liam Li Christopher Ré Ameet Talwalkar AI4CE 36 22 0 29 Mar 2021
Label-Imbalanced and Group-Sensitive Classification under Overparameterization Ganesh Ramachandra Kini Orestis Paraskevas Samet Oymak Christos Thrampoulidis 29 93 0 02 Mar 2021
On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning Bangnig Zhang Raghunandan Rajan Luis Pineda Nathan Lambert André Biedenkapp Kurtland Chua Frank Hutter Roberto Calandra 26 100 0 26 Feb 2021
CATE: Computation-aware Neural Architecture Encoding with Transformers Shen Yan Kaiqiang Song Z. Feng Mi Zhang 22 24 0 14 Feb 2021
Towards Large Scale Automated Algorithm Design by Integrating Modular Benchmarking Frameworks Amine Aziz-Alaoui Carola Doerr Johann Dréo 16 12 0 12 Feb 2021
Explaining Inference Queries with Bayesian Optimization Brandon Lockhart Jinglin Peng Weiyuan Wu Jiannan Wang Eugene Wu 21 7 0 10 Feb 2021
Hyperboost: Hyperparameter Optimization by Gradient Boosting surrogate models Jeroen van Hoof Joaquin Vanschoren BDL 38 9 0 06 Jan 2021
HyperMorph: Amortized Hyperparameter Learning for Image Registration Andrew Hoopes Malte Hoffmann Bruce Fischl John Guttag Adrian Dalca 39 128 0 04 Jan 2021
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization Valerio Perrone Huibin Shen Aida Zolic I. Shcherbatyi Amr Ahmed ... Barbara Pogorzelska Miroslav Miladinovic K. Kenthapadi Matthias Seeger Cédric Archambeau 45 16 0 15 Dec 2020
Are We Ready For Learned Cardinality Estimation? Xiaoying Wang Changbo Qu Weiyuan Wu Jiannan Wang Qingqing Zhou 37 113 0 12 Dec 2020
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation Alexander I. Cowen-Rivers Wenlong Lyu Rasul Tutunov Zhi Wang Antoine Grosnit ... A. Maraval Hao Jianye Jun Wang Jan Peters H. Ammar 27 74 0 07 Dec 2020
DORB: Dynamically Optimizing Multiple Rewards with Bandits Ramakanth Pasunuru Han Guo Joey Tianyi Zhou OffRL 32 6 0 15 Nov 2020
TrimTuner: Efficient Optimization of Machine Learning Jobs in the Cloud via Sub-Sampling Pedro Mendes Maria Casimiro Paolo Romano David Garlan 22 18 0 09 Nov 2020
Resource-Aware Pareto-Optimal Automated Machine Learning Platform Yao Yang Andrew Nam M. Nasr-Azadani Teresa Tung 16 6 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
Stochastic analysis of heterogeneous porous material with modified neural architecture search (NAS) based physics-informed neural networks using transfer learning Hongwei Guo X. Zhuang Timon Rabczuk 20 82 0 03 Oct 2020
A transfer learning metamodel using artificial neural networks applied to natural convection flows in enclosures M. Ashouri Alireza Hashemi AI4CE 8 2 0 28 Aug 2020
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice Li Yang Abdallah Shami AI4CE 20 2,032 0 30 Jul 2020
Image-driven discriminative and generative machine learning algorithms for establishing microstructure-processing relationships Wufei Ma E. Kautz Arun Baskaran Aritra Chowdhury V. Joshi B. Yener D. Lewis AI4CE 37 42 0 27 Jul 2020
An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter Optimization Yimin Huang Yujun Li Hanrong Ye Zhenguo Li Zhihua Zhang 27 7 0 11 Jul 2020
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning Matthias Feurer Katharina Eggensperger Stefan Falkner Marius Lindauer Frank Hutter 35 266 0 08 Jul 2020
Auto-CASH: Autonomous Classification Algorithm Selection with Deep Q-Network Tianyu Mu Hongzhi Wang Chunnan Wang Zheng Liang 15 1 0 07 Jul 2020
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search Linnan Wang Rodrigo Fonseca Yuandong Tian 40 126 0 01 Jul 2020
Fast and Low-cost Search for Efficient Cloud Configurations for HPC Workloads V. M. Rosário Thais A. Silva Camacho O. O. Napoli E. Borin 11 5 0 28 Jun 2020
Hippo: Taming Hyper-parameter Optimization of Deep Learning with Stage Trees Ahnjae Shin Do Yoon Kim Joo Seong Jeong Byung-Gon Chun 12 4 0 22 Jun 2020
Missing Features Reconstruction Using a Wasserstein Generative Adversarial Imputation Network Magda Friedjungová Daniel Vasata Maksym Balatsko M. Jiřina DiffM SyDa GAN 14 12 0 21 Jun 2020
Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization Xingchen Ma Matthew B. Blaschko 21 7 0 21 Jun 2020
Solving Constrained CASH Problems with ADMM Parikshit Ram Sijia Liu Deepak Vijaykeerthi Dakuo Wang Djallel Bouneffouf Gregory Bramble Horst Samulowitz Alexander G. Gray 33 3 0 17 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
Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors C. Coelho Aki Kuusela Shane Li Zhuang Hao T. Aarrestad Vladimir Loncar J. Ngadiuba M. Pierini Adrian Alan Pol S. Summers MQ 32 175 0 15 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 41 100 0 15 Jun 2020
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search Vu-Linh Nguyen Tam Le M. Yamada Michael A. Osborne AI4TS 26 37 0 13 Jun 2020
NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing Nikita Klyuchnikov I. Trofimov Ekaterina Artemova Mikhail Salnikov M. Fedorov Evgeny Burnaev VLM 13 101 0 12 Jun 2020
Few-shot Neural Architecture Search Yiyang Zhao Linnan Wang Yuandong Tian Rodrigo Fonseca Tian Guo 23 90 0 11 Jun 2020
BanditPAM: Almost Linear Time $k$ -Medoids Clustering via Multi-Armed Bandits Mo Tiwari Martin Jinye Zhang James Mayclin Sebastian Thrun Chris Piech Ilan Shomorony 25 11 0 11 Jun 2020