Practical Bayesian Optimization of Machine Learning Algorithms

13 June 2012

Papers citing "Practical Bayesian Optimization of Machine Learning Algorithms"

50 / 2,247 papers shown

Title
Active Contextual Entropy Search J. H. Metzen 18 9 0 13 Nov 2015
Training Deep Gaussian Processes using Stochastic Expectation Propagation and Probabilistic Backpropagation T. Bui José Miguel Hernández-Lobato Yingzhen Li Daniel Hernández-Lobato Richard Turner BDL GP 29 8 0 11 Nov 2015
Black-box $α$ -divergence Minimization José Miguel Hernández-Lobato Yingzhen Li Mark Rowland Daniel Hernández-Lobato T. Bui Richard Turner 23 137 0 10 Nov 2015
Sandwiching the marginal likelihood using bidirectional Monte Carlo Roger C. Grosse Zoubin Ghahramani Ryan P. Adams 24 62 0 08 Nov 2015
Optimization as Estimation with Gaussian Processes in Bandit Settings Zi Wang Bolei Zhou Stefanie Jegelka GP 35 78 0 21 Oct 2015
GLASSES: Relieving The Myopia Of Bayesian Optimisation Javier I. González Michael A. Osborne Neil D. Lawrence 16 119 0 21 Oct 2015
Optimization for Gaussian Processes via Chaining E. Contal C. Malherbe Nicolas Vayatis 47 7 0 19 Oct 2015
SentiCap: Generating Image Descriptions with Sentiments A. Mathews Lexing Xie Xuming He 26 221 0 06 Oct 2015
Tensorizing Neural Networks Alexander Novikov D. Podoprikhin A. Osokin Dmitry Vetrov 16 874 0 22 Sep 2015
Bayesian inference for spatio-temporal spike-and-slab priors Michael Riis Andersen Aki Vehtari Ole Winther Lars Kai Hansen 23 32 0 15 Sep 2015
A Markov Jump Process for More Efficient Hamiltonian Monte Carlo A. Berger M. Mudigonda M. DeWeese Jascha Narain Sohl-Dickstein 31 1 0 13 Sep 2015
Unbounded Bayesian Optimization via Regularization Bobak Shahriari Alexandre Bouchard-Coté Nando de Freitas BDL 10 69 0 14 Aug 2015
No Regret Bound for Extreme Bandits Robert Nishihara David Lopez-Paz Léon Bottou 25 9 0 12 Aug 2015
Regularized Multi-Task Learning for Multi-Dimensional Log-Density Gradient Estimation Ikko Yamane Hiroaki Sasaki Masashi Sugiyama 16 8 0 01 Aug 2015
Scalable Bayesian Inference for Excitatory Point Process Networks Scott W. Linderman Ryan P. Adams 24 58 0 12 Jul 2015
Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks Huei-Fang Yang Kevin Qinghong Lin Chu-Song Chen 27 236 0 01 Jul 2015
Compressing Convolutional Neural Networks Wenlin Chen James T. Wilson Stephen Tyree Kilian Q. Weinberger Yixin Chen 24 139 0 14 Jun 2015
Mondrian Forests for Large-Scale Regression when Uncertainty Matters Balaji Lakshminarayanan Daniel M. Roy Yee Whye Teh UQCV 24 56 0 11 Jun 2015
Spectral Representations for Convolutional Neural Networks Oren Rippel Jasper Snoek Ryan P. Adams 18 327 0 11 Jun 2015
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference Edward Meeds Max Welling 27 36 0 11 Jun 2015
Learning to Select Pre-Trained Deep Representations with Bayesian Evidence Framework Yong-Deok Kim Taewoong Jang Bohyung Han Seungjin Choi BDL 33 14 0 08 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015
Local Nonstationarity for Efficient Bayesian Optimization Ruben Martinez-Cantin 26 3 0 05 Jun 2015
Bayesian optimization for materials design P. Frazier Jialei Wang AI4CE 19 222 0 03 Jun 2015
Batch Bayesian Optimization via Local Penalization Javier I. González Zhenwen Dai Philipp Hennig Neil D. Lawrence 21 351 0 29 May 2015
APAC: Augmented PAttern Classification with Neural Networks Ikuro Sato Hiroki Nishimura Kensuke Yokoi 32 137 0 13 May 2015
Bayesian Optimization for Synthetic Gene Design Javier I. González Joseph Longworth D. James Neil D. Lawrence 25 78 0 07 May 2015
ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks Francesco Visin Kyle Kastner Kyunghyun Cho Matteo Matteucci Aaron Courville Yoshua Bengio SSeg 20 271 0 03 May 2015
Compressing Neural Networks with the Hashing Trick Wenlin Chen James T. Wilson Stephen Tyree Kilian Q. Weinberger Yixin Chen 20 1,190 0 19 Apr 2015
Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction Y. Zhang Kihyuk Sohn Ruben Villegas Gang Pan Honglak Lee ObjD 21 212 0 13 Apr 2015
LSTM: A Search Space Odyssey Klaus Greff R. Srivastava Jan Koutník Bas R. Steunebrink Jürgen Schmidhuber AI4TS VLM 21 5,255 0 13 Mar 2015
apsis - Framework for Automated Optimization of Machine Learning Hyper Parameters Frederik Diehl Andreas Jauch 23 1 0 10 Mar 2015
Deep Clustered Convolutional Kernels Minyoung Kim Luca Rigazio 32 18 0 06 Mar 2015
High Dimensional Bayesian Optimisation and Bandits via Additive Models Kirthevasan Kandasamy J. Schneider Barnabás Póczós 17 349 0 05 Mar 2015
Bayesian Optimization of Text Representations Dani Yogatama Noah A. Smith BDL 32 42 0 02 Mar 2015
Non-stochastic Best Arm Identification and Hyperparameter Optimization Kevin G. Jamieson Ameet Talwalkar 45 565 0 27 Feb 2015
Scalable Bayesian Optimization Using Deep Neural Networks Jasper Snoek Oren Rippel Kevin Swersky Ryan Kiros N. Satish N. Sundaram Md. Mostofa Ali Patwary P. Prabhat Ryan P. Adams BDL UQCV 40 1,032 0 19 Feb 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 43 937 0 18 Feb 2015
Predictive Entropy Search for Bayesian Optimization with Unknown Constraints José Miguel Hernández-Lobato M. Gelbart Matthew W. Hoffman Ryan P. Adams Zoubin Ghahramani 25 152 0 18 Feb 2015
Gradient-based Hyperparameter Optimization through Reversible Learning D. Maclaurin David Duvenaud Ryan P. Adams DD 41 935 0 11 Feb 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention Ke Xu Jimmy Ba Ryan Kiros Kyunghyun Cho Aaron Courville Ruslan Salakhutdinov R. Zemel Yoshua Bengio DiffM 115 10,006 0 10 Feb 2015
Generative Moment Matching Networks Yujia Li Kevin Swersky R. Zemel OOD GAN 27 837 0 10 Feb 2015
Regularization Path of Cross-Validation Error Lower Bounds Atsushi Shibagaki Yoshiki Suzuki Masayuki Karasuyama Ichiro Takeuchi 52 11 0 09 Feb 2015
Hyperparameter Search in Machine Learning Marc Claesen B. De Moor 25 436 0 07 Feb 2015
TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries Evan R. Sparks Ameet Talwalkar Michael Franklin Michael I. Jordan Tim Kraska 23 25 0 31 Jan 2015
Differentially Private Bayesian Optimization Matt J. Kusner Jacob R. Gardner Roman Garnett Kilian Q. Weinberger 22 52 0 16 Jan 2015
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models Michael U. Gutmann J. Corander 40 285 0 14 Jan 2015
Bayesian Optimisation for Machine Translation Yishu Miao Ziyun Wang Phil Blunsom 24 2 0 22 Dec 2014
Learning Activation Functions to Improve Deep Neural Networks Forest Agostinelli Matthew Hoffman Peter Sadowski Pierre Baldi ODL 50 472 0 21 Dec 2014
Neural Network Regularization via Robust Weight Factorization Jan Rudy Weiguang Ding Daniel Jiwoong Im Graham W. Taylor OOD 42 6 0 20 Dec 2014