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MoG-QSM: Model-based Generative Adversarial Deep Learning Network for Quantitative Susceptibility Mapping
Quantitative susceptibility mapping (QSM) estimates the underlying tissu...
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QoS-Driven Video Uplinking in NOMA-Based IoT
In recent years, with the explosive growth of visual sensors and a large...
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Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction
Automatic blood vessel extraction from 3D medical images is crucial for ...
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Partial FC: Training 10 Million Identities on a Single Machine
Face recognition has been an active and vital topic among computer visio...
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Rethinking the Extraction and Interaction of Multi-Scale Features for Vessel Segmentation
Analyzing the morphological attributes of blood vessels plays a critical...
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MAFF-Net: Filter False Positive for 3D Vehicle Detection with Multi-modal Adaptive Feature Fusion
3D vehicle detection based on multi-modal fusion is an important task of...
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RangeRCNN: Towards Fast and Accurate 3D Object Detection with Range Image Representation
We present RangeRCNN, a novel and effective 3D object detection framewor...
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Association and Caching in Relay-Assisted mmWave Networks: From A Stochastic Geometry Perspective
Limited backhaul bandwidth and blockage effects are two main factors lim...
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Augmented Bi-path Network for Few-shot Learning
Few-shot Learning (FSL) which aims to learn from few labeled training da...
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EasyQuant: Post-training Quantization via Scale Optimization
The 8 bits quantization has been widely applied to accelerate network in...
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Wasserstein Distance guided Adversarial Imitation Learning with Reward Shape Exploration
The generative adversarial imitation learning (GAIL) has provided an adv...
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When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications
Model-Agnostic Meta-Learning (MAML), a model-agnostic meta-learning meth...
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Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases
Mortality prediction of diverse rare diseases using electronic health re...
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A Graph to Graphs Framework for Retrosynthesis Prediction
A fundamental problem in computational chemistry is to find a set of rea...
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GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Molecular graph generation is a fundamental problem for drug discovery a...
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Learning to Answer Ambiguous Questions with Knowledge Graph
In the task of factoid question answering over knowledge base, many ques...
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Predictive Multi-level Patient Representations from Electronic Health Records
The advent of the Internet era has led to an explosive growth in the Ele...
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PoD: Positional Dependency-Based Word Embedding for Aspect Term Extraction
Dependency context-based word embedding jointly learns the representatio...
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Learning to Customize Language Model for Generation-based dialog systems
Personalized conversation systems have received increasing attention rec...
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Early Prediction of Sepsis From Clinical Datavia Heterogeneous Event Aggregation
Sepsis is a life-threatening condition that seriously endangers millions...
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Towards Open-Domain Named Entity Recognition via Neural Correction Models
Named Entity Recognition (NER) plays an important role in a wide range o...
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A Lightweight and Accurate Localization Algorithm Using Multiple Inertial Measurement Units
In this paper, a lightweight and accurate localization algorithm is prop...
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Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning
This paper studies recommender systems with knowledge graphs, which can ...
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Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction
Clinical outcome prediction based on the Electronic Health Record (EHR) ...
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Session-based Social Recommendation via Dynamic Graph Attention Networks
Online communities such as Facebook and Twitter are enormously popular a...
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Combating Fake News: A Survey on Identification and Mitigation Techniques
The proliferation of fake news on social media has opened up new directi...
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Efficient Spiking Neural Networks with Logarithmic Temporal Coding
A Spiking Neural Network (SNN) can be trained indirectly by first traini...
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AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
Click-through rate (CTR) prediction, which aims to predict the probabili...
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Theory of Generative Deep Learning : Probe Landscape of Empirical Error via Norm Based Capacity Control
Despite its remarkable empirical success as a highly competitive branch ...
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Towards WARSHIP: Combining Components of Brain-Inspired Computing of RSH for Image Super Resolution
Evolution of deep learning shows that some algorithmic tricks are more d...
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An Online Algorithm for Power-proportional Data Centers with Switching Cost
Recent works show that power-proportional data centers can save energy c...
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Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction
The availability of a large amount of electronic health records (EHR) pr...
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Towards Automated ICD Coding Using Deep Learning
International Classification of Diseases(ICD) is an authoritative health...
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An Attention-based Collaboration Framework for Multi-View Network Representation Learning
Learning distributed node representations in networks has been attractin...
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IOTune: A G-states Driver for Elastic Performance of Block Storage
Imagining a disk which provides baseline performance at a relatively low...
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Syntax Aware LSTM Model for Chinese Semantic Role Labeling
As for semantic role labeling (SRL) task, when it comes to utilizing par...
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Two-Bit Networks for Deep Learning on Resource-Constrained Embedded Devices
With the rapid proliferation of Internet of Things and intelligent edge ...
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Less is More: Learning Prominent and Diverse Topics for Data Summarization
Statistical topic models efficiently facilitate the exploration of large...
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Context-aware Natural Language Generation with Recurrent Neural Networks
This paper studied generating natural languages at particular contexts o...
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Two are Better than One: An Ensemble of Retrieval- and Generation-Based Dialog Systems
Open-domain human-computer conversation has attracted much attention in ...
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Dialogue Session Segmentation by Embedding-Enhanced TextTiling
In human-computer conversation systems, the context of a user-issued utt...
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Improving Color Constancy by Discounting the Variation of Camera Spectral Sensitivity
It is an ill-posed problem to recover the true scene colors from a color...
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World Knowledge as Indirect Supervision for Document Clustering
One of the key obstacles in making learning protocols realistic in appli...
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Unsupervised Word and Dependency Path Embeddings for Aspect Term Extraction
In this paper, we develop a novel approach to aspect term extraction bas...
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StalemateBreaker: A Proactive Content-Introducing Approach to Automatic Human-Computer Conversation
Existing open-domain human-computer conversation systems are typically p...
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