Tianqi Chen

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Shanghai Jiao Tong University ∙ University of Washington

Automated Backend-Aware Post-Training Quantization

Quantization is a key technique to reduce the resource requirement and i...
03/27/2021 ∙ by Ziheng Jiang, et al. ∙ 5 ∙ share

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RAILS: A Robust Adversarial Immune-inspired Learning System

Adversarial attacks against deep neural networks are continuously evolvi...
12/18/2020 ∙ by Ren Wang, et al. ∙ 0 ∙ share

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Cortex: A Compiler for Recursive Deep Learning Models

Optimizing deep learning models is generally performed in two steps: (i)...
11/02/2020 ∙ by Pratik Fegade, et al. ∙ 0 ∙ share

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Dynamic Tensor Rematerialization

Checkpointing enables training deep learning models under restricted mem...
06/17/2020 ∙ by Marisa Kirisame, et al. ∙ 102 ∙ share

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Relay: A High-Level Compiler for Deep Learning

Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
04/17/2019 ∙ by Jared Roesch, et al. ∙ 0 ∙ share

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Relay: A High-Level IR for Deep Learning

Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
04/17/2019 ∙ by Jared Roesch, et al. ∙ 0 ∙ share

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ADARES: Adaptive Resource Management for Virtual Machines

Virtual execution environments allow for consolidation of multiple appli...
12/05/2018 ∙ by Ignacio Cano, et al. ∙ 0 ∙ share

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Automating Generation of Low Precision Deep Learning Operators

State of the art deep learning models have made steady progress in the f...
10/25/2018 ∙ by Meghan Cowan, et al. ∙ 0 ∙ share

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Relay: A New IR for Machine Learning Frameworks

Machine learning powers diverse services in industry including search, t...
09/26/2018 ∙ by Jared Roesch, et al. ∙ 0 ∙ share

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VTA: An Open Hardware-Software Stack for Deep Learning

Hardware acceleration is an enabler for ubiquitous and efficient deep le...
07/11/2018 ∙ by Thierry Moreau, et al. ∙ 6 ∙ share

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Learning to Optimize Tensor Programs

We introduce a learning-based framework to optimize tensor programs for ...
05/21/2018 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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

There is an increasing need to bring machine learning to a wide diversit...
02/12/2018 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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TVM: End-to-End Optimization Stack for Deep Learning

Scalable frameworks, such as TensorFlow, MXNet, Caffe, and PyTorch drive...
02/12/2018 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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

MXNet is a multi-language machine learning (ML) library to ease the deve...
12/03/2015 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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Net2Net: Accelerating Learning via Knowledge Transfer

We introduce techniques for rapidly transferring the information stored ...
11/18/2015 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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A Complete Recipe for Stochastic Gradient MCMC

Many recent Markov chain Monte Carlo (MCMC) samplers leverage continuous...
06/15/2015 ∙ by Yi-an Ma, et al. ∙ 0 ∙ share

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Empirical Evaluation of Rectified Activations in Convolutional Network

In this paper we investigate the performance of different types of recti...
05/05/2015 ∙ by Bing Xu, et al. ∙ 0 ∙ share

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A Parallel and Efficient Algorithm for Learning to Match

Many tasks in data mining and related fields can be formalized as matchi...
10/22/2014 ∙ by Jingbo Shang, et al. ∙ 0 ∙ share

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Stochastic Gradient Hamiltonian Monte Carlo

Hamiltonian Monte Carlo (HMC) sampling methods provide a mechanism for d...
02/17/2014 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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Feature-Based Matrix Factorization

Recommender system has been more and more popular and widely used in man...
09/11/2011 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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Tianqi Chen

Featured Co-authors

Zheng Zhang

Weinan Zhang

Yong Yu

Hang Li

Ian Goodfellow

Jonathon Shlens

Mu Li

Naiyan Wang

Emily B. Fox

Zhengdong Lu

Alfred Hero

Automated Backend-Aware Post-Training Quantization

RAILS: A Robust Adversarial Immune-inspired Learning System

Cortex: A Compiler for Recursive Deep Learning Models

Dynamic Tensor Rematerialization

Relay: A High-Level Compiler for Deep Learning

Relay: A High-Level IR for Deep Learning

ADARES: Adaptive Resource Management for Virtual Machines

Automating Generation of Low Precision Deep Learning Operators

Relay: A New IR for Machine Learning Frameworks

VTA: An Open Hardware-Software Stack for Deep Learning

Learning to Optimize Tensor Programs

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

TVM: End-to-End Optimization Stack for Deep Learning

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

Net2Net: Accelerating Learning via Knowledge Transfer

A Complete Recipe for Stochastic Gradient MCMC

Empirical Evaluation of Rectified Activations in Convolutional Network

A Parallel and Efficient Algorithm for Learning to Match

Stochastic Gradient Hamiltonian Monte Carlo

Feature-Based Matrix Factorization