Scalable Bayesian Optimization Using Deep Neural Networks

19 February 2015

Md. Mostofa Ali Patwary

Papers citing "Scalable Bayesian Optimization Using Deep Neural Networks"

50 / 195 papers shown

Title
Hyperboost: Hyperparameter Optimization by Gradient Boosting surrogate models Jeroen van Hoof Joaquin Vanschoren BDL 38 9 0 06 Jan 2021
High-Dimensional Bayesian Optimization via Tree-Structured Additive Models E. Han Ishank Arora Jonathan Scarlett TPM AI4CE 33 17 0 24 Dec 2020
On the performance of deep learning for numerical optimization: an application to protein structure prediction H. Rakhshani L. Idoumghar Soheila Ghambari Julien Lepagnot Mathieu Brévilliers 19 9 0 17 Dec 2020
A Population-based Hybrid Approach to Hyperparameter Optimization for Neural Networks Marcello Serqueira Israel Mendonça Eduardo Bezerra 13 19 0 22 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
Learning the Step-size Policy for the Limited-Memory Broyden-Fletcher-Goldfarb-Shanno Algorithm Lucas N. Egidio A. Hansson B. Wahlberg 30 12 0 03 Oct 2020
Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991-2020) R. Alizadehsani M. Roshanzamir Sadiq Hussain Abbas Khosravi Afsaneh Koohestani ... M. Panahiazar S. Nahavandi D. Srinivasan A. Atiya U. Acharya OOD 28 97 0 23 Aug 2020
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems Zhe Chen Yuyan Wang Dong Lin D. Cheng Lichan Hong Ed H. Chi Claire Cui 31 16 0 17 Aug 2020
Deep Bayesian Bandits: Exploring in Online Personalized Recommendations Dalin Guo S. Ktena Ferenc Huszár Pranay K. Myana Wenzhe Shi Alykhan Tejani OffRL 35 40 0 03 Aug 2020
A Hierarchical Approach to Scaling Batch Active Search Over Structured Data Vivek Myers Peyton Greenside 36 1 0 20 Jul 2020
An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter Optimization Yimin Huang Yujun Li Hanrong Ye Zhenguo Li Zhihua Zhang 30 7 0 11 Jul 2020
Auto-CASH: Autonomous Classification Algorithm Selection with Deep Q-Network Tianyu Mu Hongzhi Wang Chunnan Wang Zheng Liang 17 1 0 07 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 13 5 0 28 Jun 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification F. Wenzel Jasper Snoek Dustin Tran Rodolphe Jenatton UQCV 33 204 0 24 Jun 2020
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks Sujay Thakur Cooper Lorsung Yaniv Yacoby Finale Doshi-Velez Weiwei Pan BDL UQCV 33 4 0 21 Jun 2020
Likelihood-Free Inference with Deep Gaussian Processes Alexander Aushev Henri Pesonen Markus Heinonen J. Corander Samuel Kaski GP 26 10 0 18 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 37 437 0 17 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
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? Shen Yan Yu Zheng Wei Ao Xiao Zeng Mi Zhang SSL AI4CE 32 100 0 12 Jun 2020
TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation Jackie Baek Vivek F. Farias 40 9 0 11 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 13 34 0 09 Jun 2020
Fair Bayesian Optimization Valerio Perrone Michele Donini Muhammad Bilal Zafar Robin Schmucker K. Kenthapadi Cédric Archambeau FaML 27 84 0 09 Jun 2020
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles Sicong Liu Junzhao Du Kaiming Nan Zimu Zhou Zhangyang Wang Yingyan Lin 32 30 0 08 Jun 2020
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge Florian Hase Matteo Aldeghi Riley J. Hickman L. Roch Alán Aspuru-Guzik 49 106 0 26 Mar 2020
Cost-aware Bayesian Optimization E. Lee Valerio Perrone Cédric Archambeau Matthias Seeger 22 56 0 22 Mar 2020
ENTMOOT: A Framework for Optimization over Ensemble Tree Models Alexander Thebelt Jan Kronqvist Miten Mistry Robert M. Lee Nathan Sudermann-Merx Ruth Misener 29 54 0 10 Mar 2020
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks Marius Hobbhahn Agustinus Kristiadi Philipp Hennig BDL UQCV 78 31 0 02 Mar 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 35 277 0 24 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 29 485 0 12 Feb 2020
Debugging Machine Learning Pipelines Raoni Lourenço J. Freire D. Shasha AI4CE 13 28 0 11 Feb 2020
Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization Lukas P. Frohlich Edgar D. Klenske Julia Vinogradska Christian Daniel Melanie Zeilinger 42 36 0 07 Feb 2020
Model Inversion Networks for Model-Based Optimization Aviral Kumar Sergey Levine OffRL 35 93 0 31 Dec 2019
Fully Bayesian Recurrent Neural Networks for Safe Reinforcement Learning Matthew Benatan Edward O. Pyzer-Knapp BDL 24 6 0 08 Nov 2019
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search Colin White Willie Neiswanger Yash Savani BDL 48 314 0 25 Oct 2019
Optimizing electrode positions in 2D Electrical Impedance Tomography using deep learning D. Smyl Dong Liu 24 34 0 21 Oct 2019
Sketch-Specific Data Augmentation for Freehand Sketch Recognition Ying Zheng H. Yao Xiaoshuai Sun Shengping Zhang Sicheng Zhao Fatih Porikli 30 15 0 14 Oct 2019
Regret Bounds for Batched Bandits Hossein Esfandiari Amin Karbasi Abbas Mehrabian Vahab Mirrokni 20 61 0 11 Oct 2019
Scalable Global Optimization via Local Bayesian Optimization Samyam Rajbhandari Michael Pearce Jacob R. Gardner Ryan D. Turner Matthias Poloczek 51 452 0 03 Oct 2019
Attacking Vision-based Perception in End-to-End Autonomous Driving Models Adith Boloor Karthik Garimella Xin He C. Gill Yevgeniy Vorobeychik Xuan Zhang AAML 19 106 0 02 Oct 2019
ReNAS:Relativistic Evaluation of Neural Architecture Search Yixing Xu Yunhe Wang Avishkar Bhoopchand Christopher Mattern A. Grabska-Barwinska Chunjing Xu Chang Xu 30 82 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
Efficient Transfer Bayesian Optimization with Auxiliary Information Tomoharu Iwata Takuma Otsuka 21 2 0 17 Sep 2019
Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters Marius Lindauer Matthias Feurer Katharina Eggensperger André Biedenkapp Frank Hutter 23 18 0 19 Aug 2019
AutoML: A Survey of the State-of-the-Art Xin He Kaiyong Zhao Xiaowen Chu 25 1,423 0 02 Aug 2019
Mixed-Variable Bayesian Optimization Erik A. Daxberger Anastasia Makarova M. Turchetta Andreas Krause 24 51 0 02 Jul 2019
Hyp-RL : Hyperparameter Optimization by Reinforcement Learning H. Jomaa Josif Grabocka Lars Schmidt-Thieme 25 65 0 27 Jun 2019
Remote Sensor Design for Visual Recognition with Convolutional Neural Networks Lucas Jaffe M. Zelinski W. Sakla 19 14 0 24 Jun 2019
Robust Regression for Safe Exploration in Control Anqi Liu Guanya Shi Soon-Jo Chung Anima Anandkumar Yisong Yue 12 59 0 13 Jun 2019
Interpretability with Accurate Small Models Abhishek Ghose Balaraman Ravindran 23 1 0 04 May 2019
An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning Yaoyao Liu Bernt Schiele Qianru Sun BDL 38 128 0 17 Apr 2019