b'Ming Zhang'

research

∙ 06/28/2022

Taxonomy and evolution predicting using deep learning in images

Molecular and morphological characters, as important parts of biological...

Jiewen Xiao, et al. ∙

research

∙ 06/07/2022

Learning to Efficiently Propagate for Reasoning on Knowledge Graphs

Path-based methods are more appealing solutions than embedding methods f...

Zhaocheng Zhu, et al. ∙

research

∙ 05/21/2022

KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification

This paper studies semi-supervised graph classification, which is an imp...

Wei Ju, et al. ∙

research

∙ 05/08/2022

End-to-End Rubbing Restoration Using Generative Adversarial Networks

Rubbing restorations are significant for preserving world cultural histo...

Gongbo Sun, et al. ∙

research

∙ 09/09/2021

Graphine: A Dataset for Graph-aware Terminology Definition Generation

Precisely defining the terminology is the first step in scientific commu...

Zequn Liu, et al. ∙

research

∙ 07/27/2021

QoS-aware User Grouping Strategy for Downlink Multi-Cell NOMA Systems

In multi-cell non-orthogonal multiple access (NOMA) systems, designing a...

Fengqian Guo, et al. ∙

research

∙ 07/01/2021

Orthonormal Product Quantization Network for Scalable Face Image Retrieval

Recently, deep hashing with Hamming distance metric has drawn increasing...

Ming Zhang, et al. ∙

research

∙ 03/26/2021

IMU Data Processing For Inertial Aided Navigation: A Recurrent Neural Network Based Approach

In this work, we propose a novel method for performing inertial aided na...

Ming Zhang, et al. ∙

research

∙ 03/17/2021

Improved Deep Classwise Hashing With Centers Similarity Learning for Image Retrieval

Deep supervised hashing for image retrieval has attracted researchers' a...

Ming Zhang, et al. ∙

research

∙ 01/21/2021

MoG-QSM: Model-based Generative Adversarial Deep Learning Network for Quantitative Susceptibility Mapping

Quantitative susceptibility mapping (QSM) estimates the underlying tissu...

Ruimin Feng, et al. ∙

research

∙ 01/15/2021

QoS-Driven Video Uplinking in NOMA-Based IoT

In recent years, with the explosive growth of visual sensors and a large...

Pengfei Ma, et al. ∙

research

∙ 12/14/2020

Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction

Automatic blood vessel extraction from 3D medical images is crucial for ...

Jiafa He, et al. ∙

research

∙ 10/11/2020

Partial FC: Training 10 Million Identities on a Single Machine

Face recognition has been an active and vital topic among computer visio...

Xiang An, et al. ∙

research

∙ 10/09/2020

Rethinking the Extraction and Interaction of Multi-Scale Features for Vessel Segmentation

Analyzing the morphological attributes of blood vessels plays a critical...

Yicheng Wu, et al. ∙

research

∙ 09/23/2020

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...

Zehan Zhang, et al. ∙

research

∙ 09/01/2020

RangeRCNN: Towards Fast and Accurate 3D Object Detection with Range Image Representation

We present RangeRCNN, a novel and effective 3D object detection framewor...

Zhidong Liang, et al. ∙

research

∙ 08/16/2020

Association and Caching in Relay-Assisted mmWave Networks: From A Stochastic Geometry Perspective

Limited backhaul bandwidth and blockage effects are two main factors lim...

Zhuojia Gu, et al. ∙

research

∙ 07/15/2020

Augmented Bi-path Network for Few-shot Learning

Few-shot Learning (FSL) which aims to learn from few labeled training da...

Baoming Yan, et al. ∙

research

∙ 06/30/2020

EasyQuant: Post-training Quantization via Scale Optimization

The 8 bits quantization has been widely applied to accelerate network in...

Di Wu, et al. ∙

research

∙ 06/05/2020

Wasserstein Distance guided Adversarial Imitation Learning with Reward Shape Exploration

The generative adversarial imitation learning (GAIL) has provided an adv...

Ming Zhang, et al. ∙

research

∙ 05/24/2020

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...

Zequn Liu, et al. ∙

research

∙ 04/11/2020

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...

Luchen Liu, et al. ∙

research

∙ 03/28/2020

A Graph to Graphs Framework for Retrosynthesis Prediction

A fundamental problem in computational chemistry is to find a set of rea...

Chence Shi, et al. ∙

research

∙ 01/26/2020

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

Molecular graph generation is a fundamental problem for drug discovery a...

Chence Shi, et al. ∙

research

∙ 12/25/2019

Learning to Answer Ambiguous Questions with Knowledge Graph

In the task of factoid question answering over knowledge base, many ques...

Yikai Zhu, et al. ∙

research

∙ 11/12/2019

Predictive Multi-level Patient Representations from Electronic Health Records

The advent of the Internet era has led to an explosive growth in the Ele...

Zichang Wang, et al. ∙

research

∙ 11/09/2019

PoD: Positional Dependency-Based Word Embedding for Aspect Term Extraction

Dependency context-based word embedding jointly learns the representatio...

Yichun Yin, et al. ∙

research

∙ 10/31/2019

Learning to Customize Language Model for Generation-based dialog systems

Personalized conversation systems have received increasing attention rec...

Yiping Song, et al. ∙

research

∙ 10/14/2019

Early Prediction of Sepsis From Clinical Datavia Heterogeneous Event Aggregation

Sepsis is a life-threatening condition that seriously endangers millions...

Luchen Liu, et al. ∙

research

∙ 09/13/2019

Towards Open-Domain Named Entity Recognition via Neural Correction Models

Named Entity Recognition (NER) plays an important role in a wide range o...

Mengdi Zhu, et al. ∙

research

∙ 09/11/2019

A Lightweight and Accurate Localization Algorithm Using Multiple Inertial Measurement Units

In this paper, a lightweight and accurate localization algorithm is prop...

Ming Zhang, et al. ∙

research

∙ 06/22/2019

Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning

This paper studies recommender systems with knowledge graphs, which can ...

Weiping Song, et al. ∙

research

∙ 03/20/2019

Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction

Clinical outcome prediction based on the Electronic Health Record (EHR) ...

Luchen Liu, et al. ∙

research

∙ 02/25/2019

Session-based Social Recommendation via Dynamic Graph Attention Networks

Online communities such as Facebook and Twitter are enormously popular a...

Weiping Song, et al. ∙

research

∙ 01/18/2019

Combating Fake News: A Survey on Identification and Mitigation Techniques

The proliferation of fake news on social media has opened up new directi...

Karishma Sharma, et al. ∙

research

∙ 11/10/2018

Efficient Spiking Neural Networks with Logarithmic Temporal Coding

A Spiking Neural Network (SNN) can be trained indirectly by first traini...

Ming Zhang, et al. ∙

research

∙ 10/29/2018

AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

Click-through rate (CTR) prediction, which aims to predict the probabili...

Weiping Song, et al. ∙

research

∙ 10/03/2018

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 ...

Wendi Xu, et al. ∙

research

∙ 10/03/2018

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...

Wendi Xu, et al. ∙

research

∙ 03/20/2018

An Online Algorithm for Power-proportional Data Centers with Switching Cost

Recent works show that power-proportional data centers can save energy c...

Ming Zhang, et al. ∙

research

∙ 03/13/2018

Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction

The availability of a large amount of electronic health records (EHR) pr...

Luchen Liu, et al. ∙

research

∙ 11/11/2017

Towards Automated ICD Coding Using Deep Learning

International Classification of Diseases(ICD) is an authoritative health...

Haoran Shi, et al. ∙

research

∙ 09/19/2017

An Attention-based Collaboration Framework for Multi-View Network Representation Learning

Learning distributed node representations in networks has been attractin...

Meng Qu, et al. ∙

research

∙ 05/10/2017

IOTune: A G-states Driver for Elastic Performance of Block Storage

Imagining a disk which provides baseline performance at a relatively low...

Tao Lu, et al. ∙

research

∙ 04/03/2017

Syntax Aware LSTM Model for Chinese Semantic Role Labeling

As for semantic role labeling (SRL) task, when it comes to utilizing par...

Feng Qian, et al. ∙

research

∙ 01/02/2017

Two-Bit Networks for Deep Learning on Resource-Constrained Embedded Devices

With the rapid proliferation of Internet of Things and intelligent edge ...

Wenjia Meng, et al. ∙

research

∙ 11/29/2016

Less is More: Learning Prominent and Diverse Topics for Data Summarization

Statistical topic models efficiently facilitate the exploration of large...

Jian Tang, et al. ∙

research

∙ 11/29/2016

Context-aware Natural Language Generation with Recurrent Neural Networks

This paper studied generating natural languages at particular contexts o...

Jian Tang, et al. ∙

research

∙ 10/23/2016

Two are Better than One: An Ensemble of Retrieval- and Generation-Based Dialog Systems

Open-domain human-computer conversation has attracted much attention in ...

Yiping Song, et al. ∙

research

∙ 10/13/2016

Dialogue Session Segmentation by Embedding-Enhanced TextTiling

In human-computer conversation systems, the context of a user-issued utt...

Yiping Song, et al. ∙

Ming Zhang

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