b'Tianqi Chen'

research

∙ 05/26/2022

Tensor Program Optimization with Probabilistic Programs

Automatic optimization for tensor programs becomes increasingly importan...

Junru Shao, et al. ∙

research

∙ 01/27/2022

Bayesian network mediation analysis with application to brain functional connectome

Brain functional connectome, the collection of interconnected neural cir...

Yize Zhao, et al. ∙

research

∙ 11/01/2021

Collage: Automated Integration of Deep Learning Backends

Strong demands for efficient deployment of Deep Learning (DL) applicatio...

Byungsoo Jeon, et al. ∙

research

∙ 10/19/2021

The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding

There is often variation in the shape and size of input data used for de...

Pratik Fegade, et al. ∙

research

∙ 08/15/2021

Deep Adversarially-Enhanced k-Nearest Neighbors

Recent works have theoretically and empirically shown that deep neural n...

Ren Wang, et al. ∙

research

∙ 06/27/2021

ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense

K-Nearest Neighbor (kNN)-based deep learning methods have been applied t...

Ren Wang, et al. ∙

research

∙ 06/27/2021

Immuno-mimetic Deep Neural Networks (Immuno-Net)

Biomimetics has played a key role in the evolution of artificial neural ...

Ren Wang, et al. ∙

research

∙ 03/27/2021

Automated Backend-Aware Post-Training Quantization

Quantization is a key technique to reduce the resource requirement and i...

Ziheng Jiang, et al. ∙

research

∙ 12/18/2020

RAILS: A Robust Adversarial Immune-inspired Learning System

Adversarial attacks against deep neural networks are continuously evolvi...

Ren Wang, et al. ∙

research

∙ 11/02/2020

Cortex: A Compiler for Recursive Deep Learning Models

Optimizing deep learning models is generally performed in two steps: (i)...

Pratik Fegade, et al. ∙

research

∙ 06/17/2020

Dynamic Tensor Rematerialization

Checkpointing enables training deep learning models under restricted mem...

Marisa Kirisame, et al. ∙

research

∙ 04/17/2019

Relay: A High-Level Compiler for Deep Learning

Frameworks for writing, compiling, and optimizing deep learning (DL) mod...

Jared Roesch, et al. ∙

research

∙ 04/17/2019

Relay: A High-Level IR for Deep Learning

Frameworks for writing, compiling, and optimizing deep learning (DL) mod...

Jared Roesch, et al. ∙

research

∙ 12/05/2018

ADARES: Adaptive Resource Management for Virtual Machines

Virtual execution environments allow for consolidation of multiple appli...

Ignacio Cano, et al. ∙

research

∙ 10/25/2018

Automating Generation of Low Precision Deep Learning Operators

State of the art deep learning models have made steady progress in the f...

Meghan Cowan, et al. ∙

research

∙ 09/26/2018

Relay: A New IR for Machine Learning Frameworks

Machine learning powers diverse services in industry including search, t...

Jared Roesch, et al. ∙

research

∙ 07/11/2018

VTA: An Open Hardware-Software Stack for Deep Learning

Hardware acceleration is an enabler for ubiquitous and efficient deep le...

Thierry Moreau, et al. ∙

research

∙ 05/21/2018

Learning to Optimize Tensor Programs

We introduce a learning-based framework to optimize tensor programs for ...

Tianqi Chen, et al. ∙

research

∙ 02/12/2018

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

There is an increasing need to bring machine learning to a wide diversit...

Tianqi Chen, et al. ∙

research

∙ 02/12/2018

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

Scalable frameworks, such as TensorFlow, MXNet, Caffe, and PyTorch drive...

Tianqi Chen, et al. ∙

research

∙ 12/03/2015

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...

Tianqi Chen, et al. ∙

research

∙ 11/18/2015

Net2Net: Accelerating Learning via Knowledge Transfer

We introduce techniques for rapidly transferring the information stored ...

Tianqi Chen, et al. ∙

research

∙ 06/15/2015

A Complete Recipe for Stochastic Gradient MCMC

Many recent Markov chain Monte Carlo (MCMC) samplers leverage continuous...

Yi-an Ma, et al. ∙

research

∙ 05/05/2015

Empirical Evaluation of Rectified Activations in Convolutional Network

In this paper we investigate the performance of different types of recti...

Bing Xu, et al. ∙

research

∙ 10/22/2014

A Parallel and Efficient Algorithm for Learning to Match

Many tasks in data mining and related fields can be formalized as matchi...

Jingbo Shang, et al. ∙

research

∙ 02/17/2014

Stochastic Gradient Hamiltonian Monte Carlo

Hamiltonian Monte Carlo (HMC) sampling methods provide a mechanism for d...

Tianqi Chen, et al. ∙

research

∙ 09/11/2011

Feature-Based Matrix Factorization

Recommender system has been more and more popular and widely used in man...

Tianqi Chen, et al. ∙

Tianqi Chen

Featured Co-authors

Zheng Zhang

Weinan Zhang

Yong Yu

Sijia Liu

Hang Li

Mu Li

Ian Goodfellow

Jonathon Shlens

Jingbo Shang

Naiyan Wang

Alfred Hero

Tensor Program Optimization with Probabilistic Programs

Bayesian network mediation analysis with application to brain functional connectome

Collage: Automated Integration of Deep Learning Backends

The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding

Deep Adversarially-Enhanced k-Nearest Neighbors

ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense

Immuno-mimetic Deep Neural Networks (Immuno-Net)

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