Mu Li

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Amazon ∙ Microsoft ∙ Carnegie Mellon University

Principal Scientist at Amazon

Featured Co-authors

Wei Chen
136 publications
Ming Zhou
101 publications
Tie-Yan Liu
99 publications
Zheng Zhang
85 publications
Wangmeng Zuo
84 publications
Radu Timofte
80 publications
Tao Qin
71 publications
Suvrit Sra
59 publications
Yao Wang
54 publications
Shiguang Shan
51 publications
Yi Zhu
44 publications

FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems

Graph neural networks (GNNs) are gaining increasing popularity as a prom...
08/26/2020 ∙ by Yuwei Hu, et al. ∙ 0 ∙ share

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CSER: Communication-efficient SGD with Error Reset

The scalability of Distributed Stochastic Gradient Descent (SGD) is toda...
07/26/2020 ∙ by Cong Xie, et al. ∙ 2 ∙ share

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Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes

BERT has recently attracted a lot of attention in natural language under...
06/24/2020 ∙ by Shuai Zheng, et al. ∙ 0 ∙ share

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Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference

Modern deep neural networks increasingly make use of features such as dy...
06/04/2020 ∙ by Haichen Shen, et al. ∙ 0 ∙ share

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Learning Context-Based Non-local Entropy Modeling for Image Compression

The entropy of the codes usually serves as the rate loss in the recent l...
05/10/2020 ∙ by Mu Li, et al. ∙ 2 ∙ share

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Improving Semantic Segmentation via Self-Training

Deep learning usually achieves the best results with complete supervisio...
04/30/2020 ∙ by Yi Zhu, et al. ∙ 8 ∙ share

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ResNeSt: Split-Attention Networks

While image classification models have recently continued to advance, mo...
04/19/2020 ∙ by Hang Zhang, et al. ∙ 16 ∙ share

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AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

We introduce AutoGluon-Tabular, an open-source AutoML framework that req...
03/13/2020 ∙ by Nick Erickson, et al. ∙ 4 ∙ share

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GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing

We present GluonCV and GluonNLP, the deep learning toolkits for computer...
07/09/2019 ∙ by Jian Guo, et al. ∙ 5 ∙ share

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A Unified Optimization Approach for CNN Model Inference on Integrated GPUs

Modern deep learning applications urge to push the model inference takin...
07/03/2019 ∙ by Leyuan Wang, et al. ∙ 0 ∙ share

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Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compression

It has long been understood that precisely estimating the probabilistic ...
06/24/2019 ∙ by Mu Li, et al. ∙ 0 ∙ share

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Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources

With an increasing demand for training powers for deep learning algorith...
04/26/2019 ∙ by Haibin Lin, et al. ∙ 12 ∙ share

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Language Models with Transformers

The Transformer architecture is superior to RNN-based models in computat...
04/20/2019 ∙ by Chenguang Wang, et al. ∙ 16 ∙ share

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Learning Content-Weighted Deep Image Compression

Learning-based lossy image compression usually involves the joint optimi...
04/01/2019 ∙ by Mu Li, et al. ∙ 10 ∙ share

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Bag of Freebies for Training Object Detection Neural Networks

Comparing with enormous research achievements targeting better image cla...
02/11/2019 ∙ by Zhi Zhang, et al. ∙ 2 ∙ share

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Bag of Tricks for Image Classification with Convolutional Neural Networks

Much of the recent progress made in image classification research can be...
12/04/2018 ∙ by Junyuan Xie, et al. ∙ 18 ∙ share

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Optimizing CNN Model Inference on CPUs

The popularity of Convolutional Neural Network (CNN) models and the ubiq...
09/07/2018 ∙ by Yizhi Liu, et al. ∙ 0 ∙ share

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Approximate Distribution Matching for Sequence-to-Sequence Learning

Sequence-to-Sequence models were introduced to tackle many real-life pro...
08/24/2018 ∙ by Wenhu Chen, et al. ∙ 2 ∙ share

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Style Transfer as Unsupervised Machine Translation

Language style transferring rephrases text with specific stylistic attri...
08/23/2018 ∙ by Zhirui Zhang, et al. ∙ 0 ∙ share

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Regularizing Neural Machine Translation by Target-bidirectional Agreement

Although Neural Machine Translation (NMT) has achieved remarkable progre...
08/13/2018 ∙ by Zhirui Zhang, et al. ∙ 0 ∙ share

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Triangular Architecture for Rare Language Translation

Neural Machine Translation (NMT) performs poor on the low-resource langu...
05/13/2018 ∙ by Shuo Ren, et al. ∙ 0 ∙ share

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Achieving Human Parity on Automatic Chinese to English News Translation

Machine translation has made rapid advances in recent years. Millions of...
03/15/2018 ∙ by Hany Hassan, et al. ∙ 0 ∙ share

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Joint Training for Neural Machine Translation Models with Monolingual Data

Monolingual data have been demonstrated to be helpful in improving trans...
03/01/2018 ∙ by Zhirui Zhang, et al. ∙ 0 ∙ share

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Shift-Net: Image Inpainting via Deep Feature Rearrangement

Deep convolutional networks (CNNs) have exhibited their potential in ima...
01/29/2018 ∙ by Zhaoyi Yan, et al. ∙ 2 ∙ share

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Efficient Trimmed Convolutional Arithmetic Encoding for Lossless Image Compression

Arithmetic encoding is an essential class of coding techniques which hav...
01/15/2018 ∙ by Mu Li, et al. ∙ 0 ∙ share

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Generative Bridging Network in Neural Sequence Prediction

Maximum Likelihood Estimation (MLE) suffers from data sparsity problem i...
06/28/2017 ∙ by Wenhu Chen, et al. ∙ 0 ∙ share

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Learning Convolutional Networks for Content-weighted Image Compression

Lossy image compression is generally formulated as a joint rate-distorti...
03/30/2017 ∙ by Mu Li, et al. ∙ 0 ∙ share

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Deep Identity-aware Transfer of Facial Attributes

This paper presents a Deep convolutional network model for Identity-Awar...
10/18/2016 ∙ by Mu Li, et al. ∙ 0 ∙ share

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Convolutional Network for Attribute-driven and Identity-preserving Human Face Generation

This paper focuses on the problem of generating human face pictures from...
08/23/2016 ∙ by Mu Li, et al. ∙ 0 ∙ share

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Implicit Distortion and Fertility Models for Attention-based Encoder-Decoder NMT Model

Neural machine translation has shown very promising results lately. Most...
01/13/2016 ∙ by Shi Feng, et al. ∙ 0 ∙ share

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Data Driven Resource Allocation for Distributed Learning

In distributed machine learning, data is dispatched to multiple machines...
12/15/2015 ∙ by Travis Dick, 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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High Performance Latent Variable Models

Latent variable models have accumulated a considerable amount of interes...
10/21/2015 ∙ by Aaron Q Li, et al. ∙ 0 ∙ share

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AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization

We study distributed stochastic convex optimization under the delayed gr...
08/20/2015 ∙ by Suvrit Sra, et al. ∙ 0 ∙ share

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Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning

Distributed computing excels at processing large scale data, but the com...
05/18/2015 ∙ by Mu Li, 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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Beyond Word-based Language Model in Statistical Machine Translation

Language model is one of the most important modules in statistical machi...
02/05/2015 ∙ by Jiajun Zhang, et al. ∙ 0 ∙ share

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