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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 ...
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Do Human Rationales Improve Machine Explanations?
Work on "learning with rationales" shows that humans providing explanati...
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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...
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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...
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SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation
Supervised training of abstractive language generation models results in...
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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...
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Active Discriminative Text Representation Learning
We propose a new active learning (AL) method for text classification wit...
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Rationale-Augmented Convolutional Neural Networks for Text Classification
We present a new Convolutional Neural Network (CNN) model for text class...
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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...
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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...
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