Practical Bayesian Optimization of Machine Learning Algorithms

13 June 2012

Papers citing "Practical Bayesian Optimization of Machine Learning Algorithms"

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Title
PipeDream: Fast and Efficient Pipeline Parallel DNN Training A. Harlap Deepak Narayanan Amar Phanishayee Vivek Seshadri Nikhil R. Devanur G. Ganger Phillip B. Gibbons AI4CE 21 252 0 08 Jun 2018
Scalable Multi-Class Bayesian Support Vector Machines for Structured and Unstructured Data Martin Wistuba Ambrish Rawat BDL 30 2 0 07 Jun 2018
New Hybrid Neuro-Evolutionary Algorithms for Renewable Energy and Facilities Management Problems L. Cornejo-Bueno 44 1 0 05 Jun 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
An Aggressive Genetic Programming Approach for Searching Neural Network Structure Under Computational Constraints Zhe Li Xuehan Xiong Zhou Ren Ning Zhang Xiaoyu Wang Tianbao Yang 34 3 0 03 Jun 2018
Long-time predictive modeling of nonlinear dynamical systems using neural networks Shaowu Pan Karthik Duraisamy 39 92 0 31 May 2018
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations Biswajit Paria Kirthevasan Kandasamy Barnabás Póczós 25 125 0 30 May 2018
Human-in-the-Loop Interpretability Prior Isaac Lage A. Ross Been Kim S. Gershman Finale Doshi-Velez 32 120 0 29 May 2018
How to Blend a Robot within a Group of Zebrafish: Achieving Social Acceptance through Real-time Calibration of a Multi-level Behavioural Model L. Cazenille Yohann Chemtob Frank Bonnet A. Gribovskiy Francesco Mondada Nicolas Bredèche J. Halloy 14 17 0 29 May 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
Maximizing acquisition functions for Bayesian optimization James T. Wilson Frank Hutter M. Deisenroth 46 240 0 25 May 2018
Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming Kirthevasan Kandasamy Willie Neiswanger Reed Zhang A. Krishnamurthy J. Schneider Barnabás Póczós 19 5 0 25 May 2018
Meta-Gradient Reinforcement Learning Zhongwen Xu H. V. Hasselt David Silver 53 324 0 24 May 2018
Efficient Relaxations for Dense CRFs with Sparse Higher Order Potentials Thomas Joy Alban Desmaison Thalaiyasingam Ajanthan Rudy Bunel Mathieu Salzmann Pushmeet Kohli Philip Torr M. P. Kumar 29 6 0 23 May 2018
Optimization, fast and slow: optimally switching between local and Bayesian optimization Mark McLeod Michael A. Osborne Stephen J. Roberts 22 42 0 22 May 2018
Neural Generative Models for Global Optimization with Gradients Louis Faury Flavian Vasile Clément Calauzènes Olivier Fercoq 14 2 0 22 May 2018
A Framework for Robot Manipulation: Skill Formalism, Meta Learning and Adaptive Control Lars Johannsmeier Malkin Gerchow Sami Haddadin 21 109 0 22 May 2018
Learning to Optimize Tensor Programs Tianqi Chen Lianmin Zheng Eddie Q. Yan Ziheng Jiang T. Moreau Luis Ceze Carlos Guestrin Arvind Krishnamurthy 25 395 0 21 May 2018
Accelerated Bayesian Optimization throughWeight-Prior Tuning A. Shilton Sunil R. Gupta Santu Rana Pratibha Vellanki Laurence Park ... David Rubin T. Dorin Alireza Vahid Murray Height Teo Slezak 17 1 0 21 May 2018
Optimizing for Generalization in Machine Learning with Cross-Validation Gradients Shane T. Barratt Rishi Sharma 19 7 0 18 May 2018
Independent Component Analysis via Energy-based and Kernel-based Mutual Dependence Measures Ze Jin David S. Matteson 18 5 0 17 May 2018
Regularization Learning Networks: Deep Learning for Tabular Datasets Ira Shavitt E. Segal AI4CE 26 20 0 16 May 2018
Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions Stefan Klus Sebastian Peitz Ingmar Schuster AI4TS 13 2 0 16 May 2018
General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learning Shiyin Wei Xiaowei Jin Hui Li AI4CE 39 39 0 13 May 2018
Towards Autonomous Reinforcement Learning: Automatic Setting of Hyper-parameters using Bayesian Optimization Juan Cruz Barsce J. Palombarini E. Martínez GP 24 33 0 12 May 2018
Vecchia approximations of Gaussian-process predictions Matthias Katzfuss J. Guinness Wenlong Gong Daniel Zilber 16 91 0 08 May 2018
Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation Saeid Asgari Taghanaki Yefeng Zheng S. Kevin Zhou Bogdan Georgescu Puneet Sharma Daguang Xu Dorin Comaniciu Ghassan Hamarneh 18 330 0 08 May 2018
Using Simulation to Improve Sample-Efficiency of Bayesian Optimization for Bipedal Robots Akshara Rai Rika Antonova Franziska Meier C. Atkeson 21 29 0 07 May 2018
PRADA: Protecting against DNN Model Stealing Attacks Mika Juuti S. Szyller Samuel Marchal Nadarajah Asokan SILM AAML 35 439 0 07 May 2018
Exploring Hyper-Parameter Optimization for Neural Machine Translation on GPU Architectures Robert V. Lim Kenneth Heafield Hieu D. Hoang M. Briers A. Malony 13 6 0 05 May 2018
The Algorithm Selection Competitions 2015 and 2017 Marius Lindauer Jan N. van Rijn Lars Kotthoff 22 38 0 03 May 2018
Graph Bayesian Optimization: Algorithms, Evaluations and Applications Jiaxu Cui Bo Yang 6 6 0 03 May 2018
PANDA: Facilitating Usable AI Development Jinyang Gao Wei Wang Meihui Zhang Gang Chen H. V. Jagadish Guoliang Li Teck Khim Ng Beng Chin Ooi Sheng Wang Jingren Zhou 30 4 0 26 Apr 2018
Semi-Supervised Learning with Declaratively Specified Entropy Constraints Haitian Sun William W. Cohen Lidong Bing 13 5 0 24 Apr 2018
Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution T. Elsken J. H. Metzen Frank Hutter 131 499 0 24 Apr 2018
Autotune: A Derivative-free Optimization Framework for Hyperparameter Tuning P. Koch Oleg Golovidov Steven Gardner B. Wujek J. Griffin Yan Xu 13 91 0 20 Apr 2018
GNAS: A Greedy Neural Architecture Search Method for Multi-Attribute Learning Siyu Huang Xi Li Zhi-Qi Cheng Zhongfei Zhang Alexander G. Hauptmann 21 56 0 19 Apr 2018
Rafiki: Machine Learning as an Analytics Service System Wei Wang Sheng Wang Jinyang Gao Meihui Zhang Gang Chen Teck Khim Ng Beng Chin Ooi 33 111 0 17 Apr 2018
Continuously Constructive Deep Neural Networks Ozan Irsoy Ethem Alpaydin 16 18 0 07 Apr 2018
Programmatically Interpretable Reinforcement Learning Abhinav Verma V. Murali Rishabh Singh Pushmeet Kohli Swarat Chaudhuri 17 347 0 06 Apr 2018
Learning Strict Identity Mappings in Deep Residual Networks Xin Yu Zhiding Yu Srikumar Ramalingam 19 17 0 05 Apr 2018
Deep Spatiotemporal Models for Robust Proprioceptive Terrain Classification Abhinav Valada Wolfram Burgard 27 61 0 02 Apr 2018
Substitute Teacher Networks: Learning with Almost No Supervision Samuel Albanie James Thewlis Joao F. Henriques 22 2 0 01 Apr 2018
Meta-Learning Update Rules for Unsupervised Representation Learning Luke Metz Niru Maheswaranathan Brian Cheung Jascha Narain Sohl-Dickstein SSL OOD 31 122 0 31 Mar 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
Stochastic Variational Inference with Gradient Linearization Tobias Plötz Anne S. Wannenwetsch Stefan Roth 14 2 0 28 Mar 2018
Efficient Image Dataset Classification Difficulty Estimation for Predicting Deep-Learning Accuracy Florian Scheidegger R. Istrate G. Mariani Luca Benini C. Bekas Cristiano Malossi VLM 37 44 0 26 Mar 2018
MLtuner: System Support for Automatic Machine Learning Tuning Henggang Cui G. Ganger Phillip B. Gibbons 16 6 0 20 Mar 2018
AutoML from Service Provider's Perspective: Multi-device, Multi-tenant Model Selection with GP-EI Chen Yu Bojan Karlas Jie Zhong Ce Zhang Ji Liu 11 6 0 17 Mar 2018