Scalable Bayesian Optimization Using Deep Neural Networks

19 February 2015

Md. Mostofa Ali Patwary

Papers citing "Scalable Bayesian Optimization Using Deep Neural Networks"

44 / 194 papers shown

Title
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions M. Mackay Paul Vicol Jonathan Lorraine David Duvenaud Roger C. Grosse 27 164 0 07 Mar 2019
Robust Grasp Planning Over Uncertain Shape Completions Jens Lundell Francesco Verdoja Ville Kyrki 3DPC 17 58 0 02 Mar 2019
NAS-Bench-101: Towards Reproducible Neural Architecture Search Chris Ying Aaron Klein Esteban Real Eric Christiansen Kevin Patrick Murphy Frank Hutter 12 673 0 25 Feb 2019
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting Artur Bekasov Iain Murray AAML BDL 20 14 0 29 Nov 2018
Practical Design Space Exploration Luigi Nardi D. Koeplinger K. Olukotun 19 86 0 11 Oct 2018
Neural Network Encapsulation Hongyang Li Xiaoyang Guo Bo Dai Wanli Ouyang Xiaogang Wang 21 51 0 11 Aug 2018
Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks Tobias Hinz Nicolás Navarro-Guerrero S. Magg S. Wermter 27 104 0 19 Jul 2018
BOCK : Bayesian Optimization with Cylindrical Kernels Changyong Oh E. Gavves Max Welling 23 135 0 05 Jun 2018
Efficient and Scalable Batch Bayesian Optimization Using K-Means Matthew J. Groves Edward O. Pyzer-Knapp 19 15 0 04 Jun 2018
Parallel Architecture and Hyperparameter Search via Successive Halving and Classification Manoj Kumar George E. Dahl Vijay Vasudevan Mohammad Norouzi 28 25 0 25 May 2018
Best arm identification in multi-armed bandits with delayed feedback Aditya Grover Todor Markov Patrick Attia Norman Jin Nicholas Perkins ... M. Chen Zi Yang Stephen J. Harris W. Chueh Stefano Ermon 27 74 0 29 Mar 2018
Ocean Eddy Identification and Tracking using Neural Networks K. Franz R. Roscher Andres Milioto Susanne Wenzel J. Kusche AI4Cl 28 69 0 20 Mar 2018
Evolutionary Architecture Search For Deep Multitask Networks J. Liang Elliot Meyerson Risto Miikkulainen 39 120 0 10 Mar 2018
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling C. Riquelme George Tucker Jasper Snoek BDL 41 365 0 26 Feb 2018
Practical Transfer Learning for Bayesian Optimization Matthias Feurer Benjamin Letham Frank Hutter E. Bakshy 55 34 0 06 Feb 2018
Improved Inception-Residual Convolutional Neural Network for Object Recognition Md. Zahangir Alom Mahmudul Hasan C. Yakopcic T. Taha V. Asari 46 116 0 28 Dec 2017
Riemannian approach to batch normalization Minhyung Cho Jaehyung Lee 29 94 0 27 Sep 2017
Connectivity Learning in Multi-Branch Networks Karim Ahmed Lorenzo Torresani 24 26 0 27 Sep 2017
Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths José Miguel Hernández-Lobato BDL 39 76 0 16 Sep 2017
Bayesian Semisupervised Learning with Deep Generative Models Jonathan Gordon José Miguel Hernández-Lobato BDL UQCV GAN 32 27 0 29 Jun 2017
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space José Miguel Hernández-Lobato James Requeima Edward O. Pyzer-Knapp Alán Aspuru-Guzik 33 178 0 06 Jun 2017
Batched Large-scale Bayesian Optimization in High-dimensional Spaces Zi Wang Clement Gehring Pushmeet Kohli Stefanie Jegelka UQCV 14 209 0 05 Jun 2017
Accelerating Neural Architecture Search using Performance Prediction Bowen Baker O. Gupta Ramesh Raskar Nikhil Naik 15 30 0 30 May 2017
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures Masanori Suganuma Shinichi Shirakawa T. Nagao 27 587 0 03 Apr 2017
High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks Krzysztof J. Geras Stacey Wolfson Yiqiu Shen Nan Wu S. G. Kim Eric Kim Laura Heacock Ujas N Parikh Linda Moy Kyunghyun Cho 34 222 0 21 Mar 2017
Evolving Deep Neural Networks Risto Miikkulainen J. Liang Elliot Meyerson Aditya Rawal Daniel Fink ... B. Raju H. Shahrzad Arshak Navruzyan Nigel P. Duffy B. Hodjat 42 884 0 01 Mar 2017
Online Meta-learning by Parallel Algorithm Competition Stefan Elfwing E. Uchibe Kenji Doya 31 22 0 24 Feb 2017
Lets keep it simple, Using simple architectures to outperform deeper and more complex architectures S. H. HasanPour Mohammad Rouhani Mohsen Fayyaz Mohammad Sabokrou 23 119 0 22 Aug 2016
Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates Ilija Ilievski Taimoor Akhtar Jiashi Feng C. Shoemaker 32 150 0 28 Jul 2016
Convolutional Residual Memory Networks Joel Ruben Antony Moniz C. Pal 31 23 0 16 Jun 2016
Deep Q-Networks for Accelerating the Training of Deep Neural Networks Jie Fu AI4CE 46 11 0 05 Jun 2016
FractalNet: Ultra-Deep Neural Networks without Residuals Gustav Larsson Michael Maire Gregory Shakhnarovich 45 933 0 24 May 2016
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets Aaron Klein Stefan Falkner Simon Bartels Philipp Hennig Frank Hutter AI4CE 35 546 0 23 May 2016
Bayesian Hyperparameter Optimization for Ensemble Learning Julien-Charles Levesque Christian Gagné R. Sabourin BDL 24 49 0 20 May 2016
Deep Residual Networks with Exponential Linear Unit Anish Shah Eashan Kadam Hena Shah Sameer Shinde Sandip Shingade 50 120 0 14 Apr 2016
Multi-Bias Non-linear Activation in Deep Neural Networks Hongyang Li Wanli Ouyang Xiaogang Wang 15 64 0 03 Apr 2016
Deep Networks with Stochastic Depth Gao Huang Yu Sun Zhuang Liu Daniel Sedra Kilian Q. Weinberger 74 2,338 0 30 Mar 2016
Do Deep Convolutional Nets Really Need to be Deep and Convolutional? G. Urban Krzysztof J. Geras Samira Ebrahimi Kahou Ozlem Aslan Shengjie Wang R. Caruana Abdel-rahman Mohamed Matthai Philipose Matthew Richardson 20 47 0 17 Mar 2016
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units Wenling Shang Kihyuk Sohn Diogo Almeida Honglak Lee 24 499 0 16 Mar 2016
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions Amar Shah Zoubin Ghahramani 35 159 0 23 Nov 2015
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 61 872 0 06 Nov 2015
Mondrian Forests for Large-Scale Regression when Uncertainty Matters Balaji Lakshminarayanan Daniel M. Roy Yee Whye Teh UQCV 32 56 0 11 Jun 2015
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 92 271 0 24 Feb 2014
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,639 0 03 Jul 2012