b'Hui Jiang'

research

∙ 06/01/2021

Exploring Dynamic Selection of Branch Expansion Orders for Code Generation

Due to the great potential in facilitating software development, code ge...

Hui Jiang, et al. ∙

research

∙ 05/13/2021

Reciprocal Feature Learning via Explicit and Implicit Tasks in Scene Text Recognition

Text recognition is a popular topic for its broad applications. In this ...

Hui Jiang, et al. ∙

research

∙ 03/05/2021

Enhanced Aspect-Based Sentiment Analysis Models with Progressive Self-supervised Attention Learning

In aspect-based sentiment analysis (ABSA), many neural models are equipp...

Jinsong Su, et al. ∙

research

∙ 06/21/2020

Match^2: A Matching over Matching Model for Similar Question Identification

Community Question Answering (CQA) has become a primary means for people...

Zizhen Wang, et al. ∙

research

∙ 02/10/2020

On Approximation Capabilities of ReLU Activation and Softmax Output Layer in Neural Networks

In this paper, we have extended the well-established universal approxima...

Behnam Asadi, et al. ∙

research

∙ 07/30/2019

Dual-FOFE-net Neural Models for Entity Linking with PageRank

This paper presents a simple and computationally efficient approach for ...

Feng Wei, et al. ∙

research

∙ 05/30/2019

Bandlimiting Neural Networks Against Adversarial Attacks

In this paper, we study the adversarial attack and defence problem in de...

Yuping Lin, et al. ∙

research

∙ 05/24/2019

Content based News Recommendation via Shortest Entity Distance over Knowledge Graphs

Content-based news recommendation systems need to recommend news article...

Kevin Joseph, et al. ∙

research

∙ 04/05/2019

Effective Context and Fragment Feature Usage for Named Entity Recognition

In this paper, we explore a new approach to named entity recognition (NE...

Nargiza Nosirova, et al. ∙

research

∙ 04/05/2019

A Multi-task Learning Approach for Named Entity Recognition using Local Detection

Named entity recognition (NER) systems that perform well require task-re...

Nargiza Nosirova, et al. ∙

research

∙ 03/29/2019

A General FOFE-net Framework for Simple and Effective Question Answering over Knowledge Bases

Question answering over knowledge base (KB-QA) has recently become a pop...

Dekun Wu, et al. ∙

research

∙ 03/06/2019

Why Learning of Large-Scale Neural Networks Behaves Like Convex Optimization

In this paper, we present some theoretical work to explain why simple gr...

Hui Jiang, et al. ∙

research

∙ 02/23/2019

Fixed-Size Ordinally Forgetting Encoding Based Word Sense Disambiguation

In this paper, we present our method of using fixed-size ordinally forge...

Xi Zhu, et al. ∙

research

∙ 01/07/2019

A New Perspective on Machine Learning: How to do Perfect Supervised Learning

In this work, we introduce the concept of bandlimiting into the theory o...

Hui Jiang, et al. ∙

research

∙ 11/16/2018

DropFilter: A Novel Regularization Method for Learning Convolutional Neural Networks

The past few years have witnessed the fast development of different regu...

Hengyue Pan, et al. ∙

research

∙ 09/10/2018

Exploring Machine Reading Comprehension with Explicit Knowledge

To apply general knowledge to machine reading comprehension (MRC), we pr...

Chao Wang, et al. ∙

research

∙ 09/08/2018

Simplified Hierarchical Recurrent Encoder-Decoder for Building End-To-End Dialogue Systems

As a generative model for building end-to-end dialogue systems, Hierarch...

Chao Wang, et al. ∙

research

∙ 07/21/2018

Distributed Layered Grant-Free Non-Orthogonal Multiple Access for Massive MTC

Grant-free transmission is considered as a promising technology to suppo...

Hui Jiang, et al. ∙

research

∙ 06/20/2018

Using Neural Network for Identifying Clickbaits in Online News Media

Online news media sometimes use misleading headlines to lure users to op...

Amin Omidvar, et al. ∙

research

∙ 03/09/2018

Accurate and Efficient Estimation of Small P-values with the Cross-Entropy Method: Applications in Genomic Data Analysis

Small p-values are often required to be accurately estimated in large sc...

Yang Shi, et al. ∙

research

∙ 08/04/2017

Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference

The RepEval 2017 Shared Task aims to evaluate natural language understan...

Qian Chen, et al. ∙

research

∙ 03/14/2017

Exploring Question Understanding and Adaptation in Neural-Network-Based Question Answering

The last several years have seen intensive interest in exploring neural-...

Junbei Zhang, et al. ∙

research

∙ 11/13/2016

Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge

In this paper, we propose commonsense knowledge enhanced embeddings (KEE...

Quan Liu, et al. ∙

research

∙ 11/11/2016

Neural Networks Models for Entity Discovery and Linking

This paper describes the USTC_NELSLIP systems submitted to the Trilingua...

Dan Liu, et al. ∙

research

∙ 11/02/2016

A FOFE-based Local Detection Approach for Named Entity Recognition and Mention Detection

In this paper, we study a novel approach for named entity recognition (N...

Mingbin Xu, et al. ∙

research

∙ 10/26/2016

Distraction-Based Neural Networks for Document Summarization

Distributed representation learned with neural networks has recently sho...

Qian Chen, et al. ∙

research

∙ 06/20/2016

Learning Convolutional Neural Networks using Hybrid Orthogonal Projection and Estimation

Convolutional neural networks (CNNs) have yielded the excellent performa...

Hengyue Pan, et al. ∙

research

∙ 04/30/2016

Higher Order Recurrent Neural Networks

In this paper, we study novel neural network structures to better model ...

Rohollah Soltani, et al. ∙

research

∙ 03/24/2016

Probabilistic Reasoning via Deep Learning: Neural Association Models

In this paper, we propose a new deep learning approach, called neural as...

Quan Liu, et al. ∙

research

∙ 03/24/2016

Part-of-Speech Relevance Weights for Learning Word Embeddings

This paper proposes a model to learn word embeddings with weighted conte...

Quan Liu, et al. ∙

research

∙ 02/16/2016

Generating images with recurrent adversarial networks

Gatys et al. (2015) showed that optimizing pixels to match features in a...

Daniel Jiwoong Im, et al. ∙

research

∙ 02/01/2016

A Deep Learning Based Fast Image Saliency Detection Algorithm

In this paper, we propose a fast deep learning method for object salienc...

Hengyue Pan, et al. ∙

research

∙ 12/28/2015

Feedforward Sequential Memory Networks: A New Structure to Learn Long-term Dependency

In this paper, we propose a novel neural network structure, namely feedf...

Shiliang Zhang, et al. ∙

research

∙ 10/09/2015

Feedforward Sequential Memory Neural Networks without Recurrent Feedback

We introduce a new structure for memory neural networks, called feedforw...

Shiliang Zhang, et al. ∙

research

∙ 06/24/2015

Leverage Financial News to Predict Stock Price Movements Using Word Embeddings and Deep Neural Networks

Financial news contains useful information on public companies and the m...

Yangtuo Peng, et al. ∙

research

∙ 05/06/2015

A Fixed-Size Encoding Method for Variable-Length Sequences with its Application to Neural Network Language Models

In this paper, we propose the new fixed-size ordinally-forgetting encodi...

Shiliang Zhang, et al. ∙

research

∙ 05/05/2015

Deep Learning for Object Saliency Detection and Image Segmentation

In this paper, we propose several novel deep learning methods for object...

Hengyue Pan, et al. ∙

research

∙ 02/03/2015

Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Probe and Learn Neural Networks

In this paper, we propose a novel model for high-dimensional data, calle...

Shiliang Zhang, et al. ∙

Hui Jiang

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