b'Di Niu'

QBSUM: a Large-Scale Query-Based Document Summarization Dataset from Real-world Applications

Query-based document summarization aims to extract or generate a summary...
10/27/2020 ∙ by Mingjun Zhao, et al. ∙ 0 ∙ share

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Neural Architecture Search For Keyword Spotting

Deep neural networks have recently become a popular solution to keyword ...
09/01/2020 ∙ by Tong Mo, et al. ∙ 0 ∙ share

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Reinforced Curriculum Learning on Pre-trained Neural Machine Translation Models

The competitive performance of neural machine translation (NMT) critical...
04/13/2020 ∙ by Mingjun Zhao, et al. ∙ 0 ∙ share

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GIANT: Scalable Creation of a Web-scale Ontology

Understanding what online users may pay attention to is key to content r...
04/05/2020 ∙ by Bang Liu, et al. ∙ 0 ∙ share

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Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus

The ability to ask questions is important in both human and machine inte...
01/27/2020 ∙ by Bang Liu, et al. ∙ 0 ∙ share

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Learning Privately over Distributed Features: An ADMM Sharing Approach

Distributed machine learning has been widely studied in order to handle ...
07/17/2019 ∙ by Yaochen Hu, et al. ∙ 0 ∙ share

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A User-Centered Concept Mining System for Query and Document Understanding at Tencent

Concepts embody the knowledge of the world and facilitate the cognitive ...
05/21/2019 ∙ by Bang Liu, et al. ∙ 0 ∙ share

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Multiresolution Graph Attention Networks for Relevance Matching

A large number of deep learning models have been proposed for the text m...
02/27/2019 ∙ by Ting Zhang, et al. ∙ 0 ∙ share

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Learning to Generate Questions by Learning What not to Generate

Automatic question generation is an important technique that can improve...
02/27/2019 ∙ by Bang Liu, et al. ∙ 0 ∙ share

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Stochastic Distributed Optimization for Machine Learning from Decentralized Features

Distributed machine learning has been widely studied in the literature t...
12/16/2018 ∙ by Yaochen Hu, et al. ∙ 0 ∙ share

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A Model Parallel Proximal Stochastic Gradient Algorithm for Partially Asynchronous Systems

Large models are prevalent in modern machine learning scenarios, includi...
10/19/2018 ∙ by Rui Zhu, et al. ∙ 0 ∙ share

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Android Malware Detection using Large-scale Network Representation Learning

With the growth of mobile devices and applications, the number of malici...
06/13/2018 ∙ by Rui Zhu, et al. ∙ 0 ∙ share

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Android Malware Detection based on Factorization Machine

With the increasing popularity of Android smart phones in recent years, ...
05/30/2018 ∙ by Chenglin Li, et al. ∙ 0 ∙ share

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House Price Modeling over Heterogeneous Regions with Hierarchical Spatial Functional Analysis

Online real-estate information systems such as Zillow and Trulia have ga...
03/01/2018 ∙ by Bang Liu, et al. ∙ 0 ∙ share

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Recover Fine-Grained Spatial Data from Coarse Aggregation

In this paper, we study a new type of spatial sparse recovery problem, t...
03/01/2018 ∙ by Bang Liu, et al. ∙ 0 ∙ share

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Growing Story Forest Online from Massive Breaking News

We describe our experience of implementing a news content organization s...
03/01/2018 ∙ by Bang Liu, et al. ∙ 0 ∙ share

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Matching Natural Language Sentences with Hierarchical Sentence Factorization

Semantic matching of natural language sentences or identifying the relat...
03/01/2018 ∙ by Bang Liu, et al. ∙ 0 ∙ share

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A Block-wise, Asynchronous and Distributed ADMM Algorithm for General Form Consensus Optimization

Many machine learning models, including those with non-smooth regularize...
02/24/2018 ∙ by Rui Zhu, et al. ∙ 0 ∙ share

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Asynchronous Stochastic Proximal Methods for Nonconvex Nonsmooth Optimization

We study stochastic algorithms for solving non-convex optimization probl...
02/24/2018 ∙ by Rui Zhu, et al. ∙ 0 ∙ share

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Matching Long Text Documents via Graph Convolutional Networks

Identifying the relationship between two text objects is a core research...
02/21/2018 ∙ by Bang Liu, et al. ∙ 0 ∙ share

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cqrReg: An R Package for Quantile and Composite Quantile Regression and Variable Selection

The cqrReg package for R is the first to introduce a family of robust, h...
09/13/2017 ∙ by Matthew Pietrosanu, et al. ∙ 0 ∙ share

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Expectile Matrix Factorization for Skewed Data Analysis

Matrix factorization is a popular approach to solving matrix estimation ...
06/07/2016 ∙ by Rui Zhu, et al. ∙ 0 ∙ share

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Di Niu

Featured Co-authors

Peng Liu

Rui Zhu

Ting Zhang

Yu Xu

Linglong Kong

Bang Liu

Hongwen Zhang

Zongpeng Li

Chenglin Li

Kunfeng Lai

Shangling Jui

QBSUM: a Large-Scale Query-Based Document Summarization Dataset from Real-world Applications

Neural Architecture Search For Keyword Spotting

Reinforced Curriculum Learning on Pre-trained Neural Machine Translation Models

GIANT: Scalable Creation of a Web-scale Ontology

Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus

Learning Privately over Distributed Features: An ADMM Sharing Approach

A User-Centered Concept Mining System for Query and Document Understanding at Tencent

Multiresolution Graph Attention Networks for Relevance Matching

Learning to Generate Questions by Learning What not to Generate

Stochastic Distributed Optimization for Machine Learning from Decentralized Features

A Model Parallel Proximal Stochastic Gradient Algorithm for Partially Asynchronous Systems

Android Malware Detection using Large-scale Network Representation Learning

Android Malware Detection based on Factorization Machine

House Price Modeling over Heterogeneous Regions with Hierarchical Spatial Functional Analysis

Recover Fine-Grained Spatial Data from Coarse Aggregation

Growing Story Forest Online from Massive Breaking News

Matching Natural Language Sentences with Hierarchical Sentence Factorization

A Block-wise, Asynchronous and Distributed ADMM Algorithm for General Form Consensus Optimization

Asynchronous Stochastic Proximal Methods for Nonconvex Nonsmooth Optimization

Matching Long Text Documents via Graph Convolutional Networks

cqrReg: An R Package for Quantile and Composite Quantile Regression and Variable Selection

Expectile Matrix Factorization for Skewed Data Analysis