Non-stochastic Best Arm Identification and Hyperparameter Optimization

27 February 2015

Papers citing "Non-stochastic Best Arm Identification and Hyperparameter Optimization"

50 / 241 papers shown

Title
Efficient Automatic CASH via Rising Bandits Yang Li Jiawei Jiang Jinyang Gao Yingxia Shao Ce Zhang Bin Cui 21 34 0 08 Dec 2020
Online Model Selection: a Rested Bandit Formulation Leonardo Cella Claudio Gentile Massimiliano Pontil 9 0 0 07 Dec 2020
MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements Yang Li Yu Shen Jiawei Jiang Jinyang Gao Ce Zhang Bin Cui 16 27 0 05 Dec 2020
Greedy k-Center from Noisy Distance Samples Neharika Jali Nikhil Karamchandani Sharayu Moharir 9 2 0 03 Nov 2020
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians Juhan Bae Roger C. Grosse 27 24 0 26 Oct 2020
Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise Cédric Renggli Luka Rimanic Luka Kolar Wentao Wu Ce Zhang 38 3 0 16 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
Binarized Neural Architecture Search for Efficient Object Recognition Hanlin Chen Lian Zhuo Baochang Zhang Xiawu Zheng Jianzhuang Liu Rongrong Ji David Doermann G. Guo MQ 10 18 0 08 Sep 2020
Automated Machine Learning -- a brief review at the end of the early years Hugo Jair Escalante 13 26 0 19 Aug 2020
Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning L. Hertel Pierre Baldi D. Gillen BDL 20 12 0 29 Jul 2020
Practical and sample efficient zero-shot HPO Fela Winkelmolen Nikita Ivkin H. Bozkurt Zohar Karnin VLM 6 13 0 27 Jul 2020
AABO: Adaptive Anchor Box Optimization for Object Detection via Bayesian Sub-sampling Wenshuo Ma Tingzhong Tian Hang Xu Yimin Huang Zhenguo Li 12 16 0 18 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
Hyperparameter Optimization in Neural Networks via Structured Sparse Recovery Minsu Cho Mohammadreza Soltani C. Hegde 14 1 0 07 Jul 2020
Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL Lucas Zimmer Marius Lindauer Frank Hutter MU 14 88 0 24 Jun 2020
Hippo: Taming Hyper-parameter Optimization of Deep Learning with Stage Trees Ahnjae Shin Do Yoon Kim Joo Seong Jeong Byung-Gon Chun 17 4 0 22 Jun 2020
SnapBoost: A Heterogeneous Boosting Machine Thomas Parnell Andreea Anghel M. Lazuka Nikolas Ioannou Sebastian Kurella Peshal Agarwal N. Papandreou Haralambos Pozidis 25 0 0 17 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
BanditPAM: Almost Linear Time $k$ -Medoids Clustering via Multi-Armed Bandits Mo Tiwari Martin Jinye Zhang James Mayclin Sebastian Thrun Chris Piech Ilan Shomorony 27 11 0 11 Jun 2020
Quantile Multi-Armed Bandits: Optimal Best-Arm Identification and a Differentially Private Scheme Konstantinos E. Nikolakakis Dionysios S. Kalogerias Or Sheffet Anand D. Sarwate 8 11 0 11 Jun 2020
Learning to Rank Learning Curves Martin Wistuba Tejaswini Pedapati 6 24 0 05 Jun 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
Model-based Asynchronous Hyperparameter and Neural Architecture Search Aaron Klein Louis C. Tiao Thibaut Lienart Cédric Archambeau Matthias Seeger 23 5 0 24 Mar 2020
Hyper-Parameter Optimization: A Review of Algorithms and Applications Tong Yu Hong Zhu AAML 21 521 0 12 Mar 2020
Meta-learning curiosity algorithms Ferran Alet Martin Schneider Tomas Lozano-Perez L. Kaelbling 25 63 0 11 Mar 2020
Neuron Shapley: Discovering the Responsible Neurons Amirata Ghorbani James Zou FAtt TDI 25 108 0 23 Feb 2020
Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping Jesse Dodge Gabriel Ilharco Roy Schwartz Ali Farhadi Hannaneh Hajishirzi Noah A. Smith 41 584 0 15 Feb 2020
NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search Arber Zela Julien N. Siems Frank Hutter 88 147 0 28 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
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline Richard Liaw Romil Bhardwaj Lisa Dunlap Yitian Zou Joseph E. Gonzalez Ion Stoica Alexey Tumanov 18 44 0 08 Jan 2020
Meta-Learning Initializations for Image Segmentation S. Hendryx Andrew B. Leach P. Hein Clayton T. Morrison VLM 10 25 0 13 Dec 2019
Stage-based Hyper-parameter Optimization for Deep Learning Ahnjae Shin Dongjin Shin Sungwoo Cho Do Yoon Kim Eunji Jeong Gyeong-In Yu Byung-Gon Chun 11 4 0 24 Nov 2019
Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine Paul Vicol David Duvenaud DD 27 403 0 06 Nov 2019
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification Xuan Wu Lingxiao Zhao Leman Akoglu 9 31 0 26 Sep 2019
Learning to Tune XGBoost with XGBoost Johanna Sommer Dimitrios Sarigiannis Thomas Parnell 13 7 0 16 Sep 2019
Weighted Sampling for Combined Model Selection and Hyperparameter Tuning Dimitrios Sarigiannis Thomas Parnell Haris Pozidis 142 3 0 16 Sep 2019
BOSH: An Efficient Meta Algorithm for Decision-based Attacks Zhenxin Xiao Puyudi Yang Yuchen Eleanor Jiang Kai-Wei Chang Cho-Jui Hsieh AAML 16 1 0 10 Sep 2019
BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters Marius Lindauer Katharina Eggensperger Matthias Feurer André Biedenkapp Joshua Marben Philip Muller Frank Hutter 5 40 0 16 Aug 2019
Optuna: A Next-generation Hyperparameter Optimization Framework Takuya Akiba Shotaro Sano Toshihiko Yanase Takeru Ohta Masanori Koyama 17 5,571 0 25 Jul 2019
Techniques for Automated Machine Learning Yi-Wei Chen Qingquan Song Xia Hu 18 48 0 21 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
Two-stage Optimization for Machine Learning Workflow Alexandre Quemy TPM 24 26 0 01 Jul 2019
One-Shot Neural Architecture Search via Compressive Sensing Minsu Cho Mohammadreza Soltani C. Hegde 22 17 0 07 Jun 2019
Automated Machine Learning: State-of-The-Art and Open Challenges Radwa El Shawi Mohamed Maher Sherif Sakr 25 158 0 05 Jun 2019
Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit Yi-Qi Hu Yang Yu Jun-Da Liao 6 9 0 31 May 2019
Meta-Surrogate Benchmarking for Hyperparameter Optimization Aaron Klein Zhenwen Dai Frank Hutter Neil D. Lawrence Javier I. González OffRL 6 36 0 30 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
AutoDispNet: Improving Disparity Estimation With AutoML Tonmoy Saikia Yassine Marrakchi Arber Zela Frank Hutter Thomas Brox 19 78 0 17 May 2019