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Automated Backend-Aware Post-Training Quantization

Mar 27, 2021
Ziheng Jiang, Animesh Jain, Andrew Liu, Josh Fromm, Chengqian Ma, Tianqi Chen, Luis Ceze

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RAILS: A Robust Adversarial Immune-inspired Learning System

Dec 18, 2020
Ren Wang, Tianqi Chen, Stephen Lindsly, Alnawaz Rehemtulla, Alfred Hero, Indika Rajapakse

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Cortex: A Compiler for Recursive Deep Learning Models

Nov 02, 2020
Pratik Fegade, Tianqi Chen, Phil Gibbons, Todd Mowry

* 11 pages, 12 figures and 6 tables 

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Dynamic Tensor Rematerialization

Jun 18, 2020
Marisa Kirisame, Steven Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared Roesch, Tianqi Chen, Zachary Tatlock

* 28 pages, 11 figures, implementation available here: 

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Relay: A High-Level IR for Deep Learning

Apr 17, 2019
Jared Roesch, Steven Lyubomirsky, Marisa Kirisame, Josh Pollock, Logan Weber, Ziheng Jiang, Tianqi Chen, Thierry Moreau, Zachary Tatlock

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ADARES: Adaptive Resource Management for Virtual Machines

Dec 06, 2018
Ignacio Cano, Lequn Chen, Pedro Fonseca, Tianqi Chen, Chern Cheah, Karan Gupta, Ramesh Chandra, Arvind Krishnamurthy

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Learning to Optimize Tensor Programs

Oct 27, 2018
Tianqi Chen, Lianmin Zheng, Eddie Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

* NIPS 2018 

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Automating Generation of Low Precision Deep Learning Operators

Oct 25, 2018
Meghan Cowan, Thierry Moreau, Tianqi Chen, Luis Ceze

* 10 pages, 11 figures 

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TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

Oct 05, 2018
Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Yan, Meghan Cowan, Haichen Shen, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

* Significantly improved version, add automated optimization 

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Relay: A New IR for Machine Learning Frameworks

Sep 26, 2018
Jared Roesch, Steven Lyubomirsky, Logan Weber, Josh Pollock, Marisa Kirisame, Tianqi Chen, Zachary Tatlock

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VTA: An Open Hardware-Software Stack for Deep Learning

Jul 11, 2018
Thierry Moreau, Tianqi Chen, Ziheng Jiang, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

* 16 pages, 2 reference pages, 16 figures 

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XGBoost: A Scalable Tree Boosting System

Jun 10, 2016
Tianqi Chen, Carlos Guestrin

* KDD'16 changed all figures to type1 

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Net2Net: Accelerating Learning via Knowledge Transfer

Apr 23, 2016
Tianqi Chen, Ian Goodfellow, Jonathon Shlens

* ICLR 2016 submission 

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Training Deep Nets with Sublinear Memory Cost

Apr 22, 2016
Tianqi Chen, Bing Xu, Chiyuan Zhang, Carlos Guestrin

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MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

Dec 03, 2015
Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang

* In Neural Information Processing Systems, Workshop on Machine Learning Systems, 2016 

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Empirical Evaluation of Rectified Activations in Convolutional Network

Nov 27, 2015
Bing Xu, Naiyan Wang, Tianqi Chen, Mu Li

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A Complete Recipe for Stochastic Gradient MCMC

Nov 01, 2015
Yi-An Ma, Tianqi Chen, Emily B. Fox

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A Parallel and Efficient Algorithm for Learning to Match

Oct 22, 2014
Jingbo Shang, Tianqi Chen, Hang Li, Zhengdong Lu, Yong Yu

* 10 pages, short version was published in ICDM 2014 

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Stochastic Gradient Hamiltonian Monte Carlo

May 12, 2014
Tianqi Chen, Emily B. Fox, Carlos Guestrin

* ICML 2014 version 

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Feature-Based Matrix Factorization

Dec 29, 2011
Tianqi Chen, Zhao Zheng, Qiuxia Lu, Weinan Zhang, Yong Yu

* Minor update, add some related works 

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