Ye Zhang

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The University of Texas at Austin ∙ Rice University

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Two new non-negativity preserving iterative regularization methods for ill-posed inverse problems

Many inverse problems are concerned with the estimation of non-negative ...
02/11/2020 ∙ by Ye Zhang, et al. ∙ 0 ∙ share

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Do Human Rationales Improve Machine Explanations?

Work on "learning with rationales" shows that humans providing explanati...
05/31/2019 ∙ by Julia Strout, et al. ∙ 0 ∙ share

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Solving Random Systems of Quadratic Equations with Tanh Wirtinger Flow

Solving quadratic systems of equations in n variables and m measurements...
05/22/2019 ∙ by Zhenwei Luo, et al. ∙ 0 ∙ share

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AceKG: A Large-scale Knowledge Graph for Academic Data Mining

Most existing knowledge graphs (KGs) in academic domains suffer from pro...
07/23/2018 ∙ by Ruijie Wang, et al. ∙ 0 ∙ share

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SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation

Supervised training of abstractive language generation models results in...
04/11/2018 ∙ by Ye Zhang, et al. ∙ 0 ∙ share

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Exploiting Domain Knowledge via Grouped Weight Sharing with Application to Text Categorization

A fundamental advantage of neural models for NLP is their ability to lea...
02/08/2017 ∙ by Ye Zhang, et al. ∙ 0 ∙ share

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Active Discriminative Text Representation Learning

We propose a new active learning (AL) method for text classification wit...
06/14/2016 ∙ by Ye Zhang, et al. ∙ 0 ∙ share

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Rationale-Augmented Convolutional Neural Networks for Text Classification

We present a new Convolutional Neural Network (CNN) model for text class...
05/14/2016 ∙ by Ye Zhang, et al. ∙ 0 ∙ share

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MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification

We introduce a novel, simple convolution neural network (CNN) architectu...
03/03/2016 ∙ by Ye Zhang, et al. ∙ 0 ∙ share

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A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification

Convolutional Neural Networks (CNNs) have recently achieved remarkably s...
10/13/2015 ∙ by Ye Zhang, et al. ∙ 0 ∙ share

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