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
Speedy Performance Estimation for Neural Architecture Search Binxin Ru Clare Lyle Lisa Schut M. Fil Mark van der Wilk Y. Gal 18 36 0 08 Jun 2020
Combinatorial Black-Box Optimization with Expert Advice Hamid Dadkhahi Karthikeyan Shanmugam Jesus Rios Payel Das Samuel C. Hoffman T. Loeffler S. Sankaranarayanan 25 16 0 06 Jun 2020
Relational Learning Analysis of Social Politics using Knowledge Graph Embedding Bilal Abu-Salih Marwan Al-Tawil Ibrahim Aljarah Hossam Faris P. Wongthongtham 22 59 0 02 Jun 2020
Gradient Monitored Reinforcement Learning Mohammed Sharafath Abdul Hameed Gavneet Singh Chadha Andreas Schwung S. Ding 33 10 0 25 May 2020
Sherpa: Robust Hyperparameter Optimization for Machine Learning L. Hertel Julian Collado Peter Sadowski J. Ott Pierre Baldi 86 103 0 08 May 2020
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch Esteban Real Chen Liang David R. So Quoc V. Le 39 220 0 06 Mar 2020
Automatic Hyper-Parameter Optimization Based on Mapping Discovery from Data to Hyper-Parameters Bozhou Chen Kaixin Zhang Longshen Ou Chenmin Ba Hongzhi Wang Chunnan Wang 16 2 0 03 Mar 2020
Denoising IMU Gyroscopes with Deep Learning for Open-Loop Attitude Estimation Martin Brossard Silvere Bonnabel Axel Barrau 24 125 0 25 Feb 2020
Neuron Shapley: Discovering the Responsible Neurons Amirata Ghorbani James Zou FAtt TDI 25 108 0 23 Feb 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 24 483 0 12 Feb 2020
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits Jack Parker-Holder Vu Nguyen Stephen J. Roberts OffRL 75 83 0 06 Feb 2020
When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions Y. Sagduyu Yi Shi T. Erpek William C. Headley Bryse Flowers G. Stantchev Zhuo Lu AAML 20 39 0 24 Jan 2020
Optimized Generic Feature Learning for Few-shot Classification across Domains Tonmoy Saikia Thomas Brox Cordelia Schmid VLM 30 48 0 22 Jan 2020
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search Xuanyi Dong Yi Yang 43 695 0 02 Jan 2020
Robust Federated Learning Through Representation Matching and Adaptive Hyper-parameters Hesham Mostafa FedML 31 39 0 30 Dec 2019
FLAML: A Fast and Lightweight AutoML Library Chi Wang Qingyun Wu Markus Weimer Erkang Zhu 30 196 0 12 Nov 2019
Adversarial Deep Learning for Over-the-Air Spectrum Poisoning Attacks Y. Sagduyu Yi Shi T. Erpek AAML 25 83 0 01 Nov 2019
DeepWiFi: Cognitive WiFi with Deep Learning Kemal Davaslioglu S. Soltani T. Erpek Y. Sagduyu 15 45 0 29 Oct 2019
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search Colin White Willie Neiswanger Yash Savani BDL 42 313 0 25 Oct 2019
ReNAS:Relativistic Evaluation of Neural Architecture Search Yixing Xu Yunhe Wang Avishkar Bhoopchand Christopher Mattern A. Grabska-Barwinska Chunjing Xu Chang Xu 27 82 0 30 Sep 2019
Towards modular and programmable architecture search Renato M. P. Negrinho Darshan Patil Nghia T. Le Daniel C. Ferreira Matthew R. Gormley Geoffrey J. Gordon 24 26 0 30 Sep 2019
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning Valerio Perrone Huibin Shen Matthias Seeger Cédric Archambeau Rodolphe Jenatton 27 96 0 27 Sep 2019
AutoML: A Survey of the State-of-the-Art Xin He Kaiyong Zhao Xiaowen Chu 20 1,420 0 02 Aug 2019
Hyperparameter Optimisation with Early Termination of Poor Performers D. Marinov Daniel Karapetyan 11 10 0 19 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
Exploration by Optimisation in Partial Monitoring Tor Lattimore Csaba Szepesvári 28 38 0 12 Jul 2019
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates Ning Liu Xiaolong Ma Zhiyuan Xu Yanzhi Wang Jian Tang Jieping Ye 40 183 0 06 Jul 2019
Mixed-Variable Bayesian Optimization Erik A. Daxberger Anastasia Makarova M. Turchetta Andreas Krause 24 51 0 02 Jul 2019
Near-Optimal Glimpse Sequences for Improved Hard Attention Neural Network Training William Harvey Michael Teng Frank Wood 31 4 0 13 Jun 2019
Model Similarity Mitigates Test Set Overuse Horia Mania John Miller Ludwig Schmidt Moritz Hardt Benjamin Recht 20 50 0 29 May 2019
The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development Micah J. Smith Carles Sala Cladellas James Max Kanter K. Veeramachaneni 24 49 0 22 May 2019
Which Tasks Should Be Learned Together in Multi-task Learning? Trevor Scott Standley Amir Zamir Dawn Chen Leonidas J. Guibas Jitendra Malik Silvio Savarese 24 502 0 18 May 2019
CrossTrainer: Practical Domain Adaptation with Loss Reweighting Justin Chen Edward Gan Kexin Rong S. Suri Peter Bailis 22 4 0 07 May 2019
The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares Rong Ge Sham Kakade Rahul Kidambi Praneeth Netrapalli 34 149 0 29 Apr 2019
Benchmark and Survey of Automated Machine Learning Frameworks Marc-André Zöller Marco F. Huber 25 86 0 26 Apr 2019
Reducing The Search Space For Hyperparameter Optimization Using Group Sparsity Minsu Cho C. Hegde 19 11 0 24 Apr 2019
An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning Yaoyao Liu Bernt Schiele Qianru Sun BDL 33 128 0 17 Apr 2019
Hyper-Parameter Tuning for the (1+(λ,λ)) GA Nguyen Dang Carola Doerr 15 21 0 09 Apr 2019
A Survey on Practical Applications of Multi-Armed and Contextual Bandits Djallel Bouneffouf Irina Rish 11 119 0 02 Apr 2019
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly Kirthevasan Kandasamy Karun Raju Vysyaraju Willie Neiswanger Biswajit Paria Christopher R. Collins J. Schneider Barnabás Póczós Eric Xing 29 174 0 15 Mar 2019
NAS-Bench-101: Towards Reproducible Neural Architecture Search Chris Ying Aaron Klein Esteban Real Eric Christiansen Kevin Patrick Murphy Frank Hutter 12 672 0 25 Feb 2019
Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives Tinu Theckel Joy Santu Rana Sunil R. Gupta Svetha Venkatesh 21 55 0 06 Feb 2019
A System for Massively Parallel Hyperparameter Tuning Liam Li Kevin G. Jamieson Afshin Rostamizadeh Ekaterina Gonina Moritz Hardt Benjamin Recht Ameet Talwalkar 24 372 0 13 Oct 2018
Safe Grid Search with Optimal Complexity Eugène Ndiaye Tam Le Olivier Fercoq Joseph Salmon Ichiro Takeuchi 38 45 0 12 Oct 2018
On Kernel Derivative Approximation with Random Fourier Features Z. Szabó Bharath K. Sriperumbudur 32 12 0 11 Oct 2018
CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms Jingwoong Kim Minkyu Kim Heungseok Park Ernar Kusdavletov Dongjun Lee A. Kim Ji-Hoon Kim Jung-Woo Ha Nako Sung 28 14 0 08 Oct 2018
OBOE: Collaborative Filtering for AutoML Model Selection Chengrun Yang Yuji Akimoto Dae Won Kim Madeleine Udell 18 100 0 09 Aug 2018
Teacher Guided Architecture Search P. Bashivan Mark Tensen J. DiCarlo 3DV 27 27 0 04 Aug 2018
Tune: A Research Platform for Distributed Model Selection and Training Richard Liaw Eric Liang Robert Nishihara Philipp Moritz Joseph E. Gonzalez Ion Stoica 19 881 0 13 Jul 2018
Bandit-Based Monte Carlo Optimization for Nearest Neighbors Vivek Bagaria Tavor Z. Baharav G. Kamath David Tse 13 12 0 21 May 2018