Practical Bayesian Optimization of Machine Learning Algorithms

13 June 2012

Papers citing "Practical Bayesian Optimization of Machine Learning Algorithms"

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Title
Variational Bayesian Monte Carlo with Noisy Likelihoods Luigi Acerbi 27 40 0 15 Jun 2020
Intra-Processing Methods for Debiasing Neural Networks Yash Savani Colin White G. NaveenSundar 16 43 0 15 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 46 100 0 15 Jun 2020
Learning Heuristic Selection with Dynamic Algorithm Configuration David Speck André Biedenkapp Frank Hutter Robert Mattmüller Marius Lindauer 27 29 0 15 Jun 2020
Improved Complexities for Stochastic Conditional Gradient Methods under Interpolation-like Conditions Tesi Xiao Krishnakumar Balasubramanian Saeed Ghadimi 25 2 0 15 Jun 2020
Meta Approach to Data Augmentation Optimization Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 32 34 0 14 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
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels Binxin Ru Xingchen Wan Xiaowen Dong Michael A. Osborne 17 21 0 13 Jun 2020
Generalizing Gain Penalization for Feature Selection in Tree-based Models Bruna D. Wundervald Andrew C. Parnell Katarina Domijan 22 6 0 12 Jun 2020
Uncertainty quantification using martingales for misspecified Gaussian processes Willie Neiswanger Aaditya Ramdas UQCV 14 14 0 12 Jun 2020
Optimizing generalization on the train set: a novel gradient-based framework to train parameters and hyperparameters simultaneously Karim Lounici Katia Méziani Benjamin Riu 35 1 0 11 Jun 2020
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning Sijia Liu Pin-Yu Chen B. Kailkhura Gaoyuan Zhang A. Hero III P. Varshney 26 224 0 11 Jun 2020
Model-Size Reduction for Reservoir Computing by Concatenating Internal States Through Time Yusuke Sakemi K. Morino T. Leleu Kazuyuki Aihara 29 20 0 11 Jun 2020
Dataset Condensation with Gradient Matching Bo Zhao Konda Reddy Mopuri Hakan Bilen DD 41 481 0 10 Jun 2020
Toward Building Safer Smart Homes for the People with Disabilities Shahinur Alam M. Mahmud M. Yeasin 16 4 0 10 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 15 34 0 09 Jun 2020
Adaptation Strategies for Automated Machine Learning on Evolving Data B. Celik Joaquin Vanschoren 27 52 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
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation Julian Berk Sunil R. Gupta Santu Rana Svetha Venkatesh 26 38 0 08 Jun 2020
Efficient AutoML Pipeline Search with Matrix and Tensor Factorization Chengrun Yang Jicong Fan Ziyang Wu Madeleine Udell 27 8 0 07 Jun 2020
Steganography GAN: Cracking Steganography with Cycle Generative Adversarial Networks Nibraas Khan Ruj Haan George Boktor Michael Mccomas Ramin Daneshi GAN 14 3 0 07 Jun 2020
Sparse representation for damage identification of structural systems Zhao Chen Hao Sun 6 17 0 06 Jun 2020
AutoHAS: Efficient Hyperparameter and Architecture Search Xuanyi Dong Mingxing Tan Adams Wei Yu Daiyi Peng Bogdan Gabrys Quoc V. Le TPM 27 23 0 05 Jun 2020
An Ergodic Measure for Active Learning From Equilibrium Ian Abraham A. Prabhakar Todd D. Murphey 26 22 0 05 Jun 2020
Bayesian optimization for modular black-box systems with switching costs Chi-Heng Lin Joseph D. Miano Eva L. Dyer 13 5 0 04 Jun 2020
Autonomous Materials Discovery Driven by Gaussian Process Regression with Inhomogeneous Measurement Noise and Anisotropic Kernels M. Noack G. Doerk Ruipeng Li Jason K. Streit R. Vaia Kevin Yager M. Fukuto 28 70 0 03 Jun 2020
Automatic Setting of DNN Hyper-Parameters by Mixing Bayesian Optimization and Tuning Rules Michele Fraccaroli E. Lamma Fabrizio Riguzzi BDL 16 2 0 03 Jun 2020
A Scalable and Cloud-Native Hyperparameter Tuning System Johnu George Ce Gao Richard Liu Hou Gang Liu Yuan Tang Ramdoot Pydipaty Amit Kumar Saha 13 13 0 03 Jun 2020
Hierarchical forecast reconciliation with machine learning Evangelos Spiliotis M. Abolghasemi Rob J. Hyndman F. Petropoulos Vassilios Assimakopoulos 14 46 0 03 Jun 2020
Geometric Graph Representations and Geometric Graph Convolutions for Deep Learning on Three-Dimensional (3D) Graphs Daniel T. Chang GNN 23 3 0 02 Jun 2020
Feature-weighted elastic net: using "features of features" for better prediction J. K. Tay N. Aghaeepour Trevor Hastie Robert Tibshirani 4 13 0 02 Jun 2020
Hyperparameter optimization with REINFORCE and Transformers C. Krishna Ashish Gupta Swarnim Narayan Himanshu Rai Diksha Manchanda 19 2 0 01 Jun 2020
Data-Driven Methods to Monitor, Model, Forecast and Control Covid-19 Pandemic: Leveraging Data Science, Epidemiology and Control Theory Teodoro Alamo Daniel Gutiérrez-Reina P. Millán 19 27 0 01 Jun 2020
Semi-supervised Embedding Learning for High-dimensional Bayesian Optimization Jingfan Chen Guanghui Zhu Chun Yuan Yihua Huang 25 15 0 29 May 2020
Machine Learning for Condensed Matter Physics Edwin Bedolla L. C. Padierna R. Castañeda-Priego AI4CE 28 66 0 28 May 2020
From Prediction to Prescription: Evolutionary Optimization of Non-Pharmaceutical Interventions in the COVID-19 Pandemic Risto Miikkulainen Olivier Francon Elliot Meyerson Xin Qiu Elisa Canzani B. Hodjat 29 3 0 28 May 2020
Is deeper better? It depends on locality of relevant features Takashi Mori Masahito Ueda OOD 25 4 0 26 May 2020
Fast differentiable DNA and protein sequence optimization for molecular design Johannes Linder Georg Seelig 41 54 0 22 May 2020
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties J. Lindinger David Reeb C. Lippert Barbara Rakitsch BDL UQCV 25 8 0 22 May 2020
Global Optimization of Gaussian processes Artur M. Schweidtmann D. Bongartz D. Grothe Tim Kerkenhoff Xiaopeng Lin J. Najman Alexander Mitsos 12 40 0 21 May 2020
HyperSTAR: Task-Aware Hyperparameters for Deep Networks Gaurav Mittal Chang Liu Nikolaos Karianakis Victor Fragoso Mei Chen Y. Fu VLM 48 23 0 21 May 2020
Rethinking Performance Estimation in Neural Architecture Search Xiawu Zheng Rongrong Ji Qiang-qiang Wang QiXiang Ye Zhenguo Li Yonghong Tian Q. Tian 24 17 0 20 May 2020
Reliability and Robustness analysis of Machine Learning based Phishing URL Detectors Bushra Sabir Muhammad Ali Babar R. Gaire A. Abuadbba AAML 35 10 0 18 May 2020
Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones? Nadezhda Chirkova E. Lobacheva Dmitry Vetrov OOD MoE 34 9 0 14 May 2020
Real-time Facial Expression Recognition "In The Wild'' by Disentangling 3D Expression from Identity Mohammad Rami Koujan L. Alharbawee Giorgos Giannakakis N. Pugeault A. Roussos CVBM 3DH 33 30 0 12 May 2020
Using Bayesian Optimization to Accelerate Virtual Screening for the Discovery of Therapeutics Appropriate for Repurposing for COVID-19 Edward O. Pyzer-Knapp 25 7 0 11 May 2020
Ensembled sparse-input hierarchical networks for high-dimensional datasets Jean Feng N. Simon 19 4 0 11 May 2020
Sequential Gallery for Interactive Visual Design Optimization Yuki Koyama Issei Sato Masataka Goto 30 76 0 08 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
Amortized Bayesian Inference for Models of Cognition Stefan T. Radev A. Voss Eva Marie Wieschen Paul-Christian Bürkner 6 5 0 08 May 2020