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Match^2: A Matching over Matching Model for Similar Question Identification
Community Question Answering (CQA) has become a primary means for people...
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On Approximation Capabilities of ReLU Activation and Softmax Output Layer in Neural Networks
In this paper, we have extended the well-established universal approxima...
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Dual-FOFE-net Neural Models for Entity Linking with PageRank
This paper presents a simple and computationally efficient approach for ...
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Bandlimiting Neural Networks Against Adversarial Attacks
In this paper, we study the adversarial attack and defence problem in de...
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Content based News Recommendation via Shortest Entity Distance over Knowledge Graphs
Content-based news recommendation systems need to recommend news article...
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Effective Context and Fragment Feature Usage for Named Entity Recognition
In this paper, we explore a new approach to named entity recognition (NE...
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A Multi-task Learning Approach for Named Entity Recognition using Local Detection
Named entity recognition (NER) systems that perform well require task-re...
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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...
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Why Learning of Large-Scale Neural Networks Behaves Like Convex Optimization
In this paper, we present some theoretical work to explain why simple gr...
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Fixed-Size Ordinally Forgetting Encoding Based Word Sense Disambiguation
In this paper, we present our method of using fixed-size ordinally forge...
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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...
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DropFilter: A Novel Regularization Method for Learning Convolutional Neural Networks
The past few years have witnessed the fast development of different regu...
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Exploring Machine Reading Comprehension with Explicit Knowledge
To apply general knowledge to machine reading comprehension (MRC), we pr...
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Simplified Hierarchical Recurrent Encoder-Decoder for Building End-To-End Dialogue Systems
As a generative model for building end-to-end dialogue systems, Hierarch...
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Distributed Layered Grant-Free Non-Orthogonal Multiple Access for Massive MTC
Grant-free transmission is considered as a promising technology to suppo...
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Using Neural Network for Identifying Clickbaits in Online News Media
Online news media sometimes use misleading headlines to lure users to op...
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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...
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Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference
The RepEval 2017 Shared Task aims to evaluate natural language understan...
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Exploring Question Understanding and Adaptation in Neural-Network-Based Question Answering
The last several years have seen intensive interest in exploring neural-...
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Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge
In this paper, we propose commonsense knowledge enhanced embeddings (KEE...
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Neural Networks Models for Entity Discovery and Linking
This paper describes the USTC_NELSLIP systems submitted to the Trilingua...
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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...
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Distraction-Based Neural Networks for Document Summarization
Distributed representation learned with neural networks has recently sho...
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Learning Convolutional Neural Networks using Hybrid Orthogonal Projection and Estimation
Convolutional neural networks (CNNs) have yielded the excellent performa...
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Higher Order Recurrent Neural Networks
In this paper, we study novel neural network structures to better model ...
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Probabilistic Reasoning via Deep Learning: Neural Association Models
In this paper, we propose a new deep learning approach, called neural as...
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Part-of-Speech Relevance Weights for Learning Word Embeddings
This paper proposes a model to learn word embeddings with weighted conte...
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Generating images with recurrent adversarial networks
Gatys et al. (2015) showed that optimizing pixels to match features in a...
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A Deep Learning Based Fast Image Saliency Detection Algorithm
In this paper, we propose a fast deep learning method for object salienc...
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Feedforward Sequential Memory Networks: A New Structure to Learn Long-term Dependency
In this paper, we propose a novel neural network structure, namely feedf...
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Feedforward Sequential Memory Neural Networks without Recurrent Feedback
We introduce a new structure for memory neural networks, called feedforw...
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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...
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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...
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Deep Learning for Object Saliency Detection and Image Segmentation
In this paper, we propose several novel deep learning methods for object...
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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...
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