Tune: A Research Platform for Distributed Model Selection and Training

13 July 2018

Papers citing "Tune: A Research Platform for Distributed Model Selection and Training"

29 / 129 papers shown

Title
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations Keir Adams L. Pattanaik Connor W. Coley 31 32 0 08 Oct 2021
Colmena: Scalable Machine-Learning-Based Steering of Ensemble Simulations for High Performance Computing Logan T. Ward Ganesh Sivaraman J. G. Pauloski Y. Babuji Ryan Chard ... R. Assary Kyle Chard L. Curtiss R. Thakur Ian Foster 27 39 0 06 Oct 2021
Matching with Transformers in MELT S. Hertling Jan Portisch Heiko Paulheim 26 9 0 15 Sep 2021
Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning Alexander J. M. Kell S. McGough M. Forshaw 11 2 0 10 Sep 2021
Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption A. Frikha Denis Krompass Volker Tresp OOD 35 1 0 09 Sep 2021
Towards Efficient and Data Agnostic Image Classification Training Pipeline for Embedded Systems K. Prokofiev V. Sovrasov 3DH 19 2 0 16 Aug 2021
HyperJump: Accelerating HyperBand via Risk Modelling Pedro Mendes Maria Casimiro Paolo Romano David Garlan 22 8 0 05 Aug 2021
Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts Dominik Scheinert L. Thamsen Houkun Zhu Jonathan Will Alexander Acker Thorsten Wittkopp O. Kao 14 15 0 29 Jul 2021
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition Yang Li Yu Shen Wentao Zhang Jiawei Jiang Bolin Ding ... Jingren Zhou Zhi-Xin Yang Wentao Wu Ce Zhang Bin Cui LRM 29 44 0 19 Jul 2021
Model-Parallel Model Selection for Deep Learning Systems Kabir Nagrecha 37 16 0 14 Jul 2021
GRAND: Graph Neural Diffusion B. Chamberlain J. Rowbottom Maria I. Gorinova Stefan Webb Emanuele Rossi M. Bronstein GNN 54 254 0 21 Jun 2021
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better Gaurav Menghani VLM MedIm 23 366 0 16 Jun 2021
Credit Assignment in Neural Networks through Deep Feedback Control Alexander Meulemans Matilde Tristany Farinha Javier García Ordónez Pau Vilimelis Aceituno João Sacramento Benjamin Grewe 31 35 0 15 Jun 2021
Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding Andrew Jesson Sören Mindermann Y. Gal Uri Shalit CML 21 53 0 08 Mar 2021
MIMOSA: Reducing Malware Analysis Overhead with Coverings Mohsen Ahmadi Kevin Leach Ryan E. Dougherty Stephanie Forrest Westley Weimer 12 8 0 18 Jan 2021
Generalized Latency Performance Estimation for Once-For-All Neural Architecture Search Muhtadyuzzaman Syed A. Srinivasan 18 9 0 04 Jan 2021
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians Juhan Bae Roger C. Grosse 27 24 0 26 Oct 2020
Rethinking CNN Models for Audio Classification Kamalesh Palanisamy Dipika Singhania Angela Yao SSL 33 144 0 22 Jul 2020
Hippo: Taming Hyper-parameter Optimization of Deep Learning with Stage Trees Ahnjae Shin Do Yoon Kim Joo Seong Jeong Byung-Gon Chun 20 4 0 22 Jun 2020
Sherpa: Robust Hyperparameter Optimization for Machine Learning L. Hertel Julian Collado Peter Sadowski J. Ott Pierre Baldi 86 103 0 08 May 2020
How Useful is Self-Supervised Pretraining for Visual Tasks? Alejandro Newell Jia Deng SSL 25 136 0 31 Mar 2020
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits Jack Parker-Holder Vu Nguyen Stephen J. Roberts OffRL 75 83 0 06 Feb 2020
SLM Lab: A Comprehensive Benchmark and Modular Software Framework for Reproducible Deep Reinforcement Learning Keng Wah Loon L. Graesser Milan Cvitkovic OffRL 21 13 0 28 Dec 2019
NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning Ameer Haj-Ali Nesreen Ahmed Theodore L. Willke Sophia Shao Krste Asanović Ion Stoica 25 101 0 20 Sep 2019
Countering the Effects of Lead Bias in News Summarization via Multi-Stage Training and Auxiliary Losses Matt Grenander Yue Dong Jackie C.K. Cheung Annie Louis 22 35 0 08 Sep 2019
Techniques for Automated Machine Learning Yi-Wei Chen Qingquan Song Xia Hu 18 48 0 21 Jul 2019
A System for Massively Parallel Hyperparameter Tuning Liam Li Kevin G. Jamieson Afshin Rostamizadeh Ekaterina Gonina Moritz Hardt Benjamin Recht Ameet Talwalkar 24 372 0 13 Oct 2018
CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms Jingwoong Kim Minkyu Kim Heungseok Park Ernar Kusdavletov Dongjun Lee A. Kim Ji-Hoon Kim Jung-Woo Ha Nako Sung 31 14 0 08 Oct 2018
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 271 5,330 0 05 Nov 2016