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A prognostic dynamic model applicable to infectious diseases providing easily visualized guides – A case study of COVID-19 in the UK
A reasonable prediction of infectious diseases transmission process unde...
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Dynamic Data Selection for Curriculum Learning via Ability Estimation
Curriculum learning methods typically rely on heuristics to estimate the...
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Conversational Semantic Parsing for Dialog State Tracking
We consider a new perspective on dialog state tracking (DST), the task o...
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Neural Data-to-Text Generation with Dynamic Content Planning
Neural data-to-text generation models have achieved significant advancem...
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Calibrating Structured Output Predictors for Natural Language Processing
We address the problem of calibrating prediction confidence for output e...
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Improved Pretraining for Domain-specific Contextual Embedding Models
We investigate methods to mitigate catastrophic forgetting during domain...
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MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low Resource Machine Translation
Manipulating training data leads to robust neural models for MT....
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ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network
Automated ICD coding, which assigns the International Classification of ...
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Large-scale Gastric Cancer Screening and Localization Using Multi-task Deep Neural Network
Gastric cancer is one of the most common cancers, which ranks third amon...
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Generating Classical Chinese Poems from Vernacular Chinese
Classical Chinese poetry is a jewel in the treasure house of Chinese cul...
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Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds
Incorporating Item Response Theory (IRT) into NLP tasks can provide valu...
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HYPE: A High Performing NLP System for Automatically Detecting Hypoglycemia Events from Electronic Health Record Notes
Hypoglycemia is common and potentially dangerous among those treated for...
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Language Identification with Deep Bottleneck Features
In this paper we proposed an end-to-end short utterances speech language...
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Deep Neural Network for Analysis of DNA Methylation Data
Many researches demonstrated that the DNA methylation, which occurs in t...
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Histogram Transform-based Speaker Identification
A novel text-independent speaker identification (SI) method is proposed....
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Sentence Simplification with Memory-Augmented Neural Networks
Sentence simplification aims to simplify the content and structure of co...
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Meta Networks
Neural networks have been successfully applied in applications with a la...
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Unsupervised Ensemble Ranking of Terms in Electronic Health Record Notes Based on Their Importance to Patients
Background: Electronic health record (EHR) notes contain abundant medica...
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CIFT: Crowd-Informed Fine-Tuning to Improve Machine Learning Ability
Item Response Theory (IRT) allows for measuring ability of Machine Learn...
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An Analysis of Ability in Deep Neural Networks
Deep neural networks (DNNs) have made significant progress in a number o...
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Ranking medical jargon in electronic health record notes by adapted distant supervision
Objective: Allowing patients to access their own electronic health recor...
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Learning to Rank Scientific Documents from the Crowd
Finding related published articles is an important task in any science, ...
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Reasoning with Memory Augmented Neural Networks for Language Comprehension
Hypothesis testing is an important cognitive process that supports human...
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Structured prediction models for RNN based sequence labeling in clinical text
Sequence labeling is a widely used method for named entity recognition a...
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Neural Tree Indexers for Text Understanding
Recurrent neural networks (RNNs) process input text sequentially and mod...
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Neural Semantic Encoders
We present a memory augmented neural network for natural language unders...
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Learning for Biomedical Information Extraction: Methodological Review of Recent Advances
Biomedical information extraction (BioIE) is important to many applicati...
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Bidirectional Recurrent Neural Networks for Medical Event Detection in Electronic Health Records
Sequence labeling for extraction of medical events and their attributes ...
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Building an Evaluation Scale using Item Response Theory
Evaluation of NLP methods requires testing against a previously vetted g...
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Heuristic algorithms for finding distribution reducts in probabilistic rough set model
Attribute reduction is one of the most important topics in rough set the...
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