Mu Li

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Amazon ∙ Microsoft ∙ Carnegie Mellon University

Principal Scientist at Amazon

Improving Machine Reading Comprehension with Single-choice Decision and Transfer Learning

Multi-choice Machine Reading Comprehension (MMRC) aims to select the cor...
11/06/2020 ∙ by Yufan Jiang, et al. ∙ 0 ∙ share

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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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Mu Li

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