Search Results for author: Ming Zhang

Found 106 papers, 36 papers with code

Pathway2Text: Dataset and Method for Biomedical Pathway Description Generation

1 code implementation Findings (NAACL) 2022 Junwei Yang, Zequn Liu, Ming Zhang, Sheng Wang

Collectively, we envision our method will become an important benchmark for evaluating Graph2Text methods and advance biomedical research for complex diseases.

named-entity-recognition Named Entity Recognition +2

Focus-Driven Contrastive Learning for Medical Question Summarization

no code implementations COLING 2022 Ming Zhang, Shuai Dou, Ziyang Wang, Yunfang Wu

Automatic medical question summarization can significantly help the system to understand consumer health questions and retrieve correct answers.

Contrastive Learning

ALEX: Towards Effective Graph Transfer Learning with Noisy Labels

no code implementations26 Sep 2023 Jingyang Yuan, Xiao Luo, Yifang Qin, Zhengyang Mao, Wei Ju, Ming Zhang

Nevertheless, the majority of GNN-based approaches have been examined using well-annotated benchmark datasets, leading to suboptimal performance in real-world graph learning scenarios.

Contrastive Learning Graph Learning +2

Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting

no code implementations21 Sep 2023 Yusheng Zhao, Xiao Luo, Wei Ju, Chong Chen, Xian-Sheng Hua, Ming Zhang

This paper studies the problem of traffic flow forecasting, which aims to predict future traffic conditions on the basis of road networks and traffic conditions in the past.

Redundancy-Free Self-Supervised Relational Learning for Graph Clustering

1 code implementation9 Sep 2023 Si-Yu Yi, Wei Ju, Yifang Qin, Xiao Luo, Luchen Liu, Yong-Dao Zhou, Ming Zhang

Graph clustering, which learns the node representations for effective cluster assignments, is a fundamental yet challenging task in data analysis and has received considerable attention accompanied by graph neural networks in recent years.

Clustering Graph Clustering +1

FIMO: A Challenge Formal Dataset for Automated Theorem Proving

no code implementations8 Sep 2023 Chengwu Liu, Jianhao Shen, Huajian Xin, Zhengying Liu, Ye Yuan, Haiming Wang, Wei Ju, Chuanyang Zheng, Yichun Yin, Lin Li, Ming Zhang, Qun Liu

We present FIMO, an innovative dataset comprising formal mathematical problem statements sourced from the International Mathematical Olympiad (IMO) Shortlisted Problems.

Automated Theorem Proving

Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts

no code implementations31 Aug 2023 Siyu Yi, Zhengyang Mao, Wei Ju, Yongdao Zhou, Luchen Liu, Xiao Luo, Ming Zhang

Graph classification, aiming at learning the graph-level representations for effective class assignments, has received outstanding achievements, which heavily relies on high-quality datasets that have balanced class distribution.

Contrastive Learning Graph Classification +2

RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification

no code implementations4 Aug 2023 Zhengyang Mao, Wei Ju, Yifang Qin, Xiao Luo, Ming Zhang

Recent approaches mainly focus on re-balancing different classes during model training, which fails to explicitly introduce new knowledge and sacrifices the performance of the head classes.

Graph Classification Retrieval

Learning on Graphs under Label Noise

no code implementations14 Jun 2023 Jingyang Yuan, Xiao Luo, Yifang Qin, Yusheng Zhao, Wei Ju, Ming Zhang

Since this regularization term cannot utilize label information, it can enhance the robustness of node representations to label noise.

Anomaly Detection Contrastive Learning +2

Towards Semi-supervised Universal Graph Classification

no code implementations31 May 2023 Xiao Luo, Yusheng Zhao, Yifang Qin, Wei Ju, Ming Zhang

To tackle class shifts, we estimate the certainty of unlabeled graphs using multiple subgraphs, which facilities the discovery of unlabeled data from unknown categories.

Graph Classification

MolXPT: Wrapping Molecules with Text for Generative Pre-training

no code implementations18 May 2023 Zequn Liu, Wei zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang, Tie-Yan Liu

Considering that text is the most important record for scientific discovery, in this paper, we propose MolXPT, a unified language model of text and molecules pre-trained on SMILES (a sequence representation of molecules) wrapped by text.

Language Modelling Molecular Property Prediction +3

TGNN: A Joint Semi-supervised Framework for Graph-level Classification

no code implementations23 Apr 2023 Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang

The two twin modules collaborate with each other by exchanging instance similarity knowledge to fully explore the structure information of both labeled and unlabeled data.

Graph Classification

A Diffusion model for POI recommendation

no code implementations14 Apr 2023 Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo, Ming Zhang

In this paper, we propose Diff-POI: a Diffusion-based model that samples the user's spatial preference for the next POI recommendation.

Learning Graph ODE for Continuous-Time Sequential Recommendation

no code implementations14 Apr 2023 Yifang Qin, Wei Ju, Hongjun Wu, Xiao Luo, Ming Zhang

Technically, GDERec is characterized by an autoregressive graph ordinary differential equation consisting of two components, which are parameterized by two tailored graph neural networks (GNNs) respectively to capture user preference from the perspective of hybrid dynamical systems.

Sequential Recommendation

A Comprehensive Survey on Deep Graph Representation Learning

no code implementations11 Apr 2023 Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Xiao Luo, Ming Zhang

Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been widely studied in a range of fields, including machine learning and data mining.

Graph Embedding Graph Representation Learning

Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data

1 code implementation29 Mar 2023 Bin Feng, Tenglong Ao, Zequn Liu, Wei Ju, Libin Liu, Ming Zhang

How to automatically synthesize natural-looking dance movements based on a piece of music is an incrementally popular yet challenging task.


GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow

1 code implementation23 Feb 2023 Fang Sun, Zhihao Zhan, Hongyu Guo, Ming Zhang, Jian Tang

In particular, GraphVF represents the first controllable geometry-aware, protein-specific molecule generation method, which can generate binding 3D molecules with tailored sub-structures and physio-chemical properties.

3D Molecule Generation Drug Discovery

2D Human Pose Estimation with Explicit Anatomical Keypoints Structure Constraints

no code implementations5 Dec 2022 Zhangjian Ji, Zilong Wang, Ming Zhang, Yapeng Chen, Yuhua Qian

Recently, human pose estimation mainly focuses on how to design a more effective and better deep network structure as human features extractor, and most designed feature extraction networks only introduce the position of each anatomical keypoint to guide their training process.

2D Human Pose Estimation Pose Estimation

TIER-A: Denoising Learning Framework for Information Extraction

no code implementations13 Nov 2022 Yongkang Li, Ming Zhang

Our framework consists of several neural models with identical structures.


GLCC: A General Framework for Graph-Level Clustering

no code implementations21 Oct 2022 Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang

In this paper, we propose a general graph-level clustering framework named Graph-Level Contrastive Clustering (GLCC) given multiple graphs.

Clustering Contrastive Learning +2

Kernel-based Substructure Exploration for Next POI Recommendation

1 code implementation8 Oct 2022 Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, Ming Zhang

To tackle the above issues, we propose a Kernel-Based Graph Neural Network (KBGNN) for next POI recommendation, which combines the characteristics of both geographical and sequential influences in a collaborative way.

Recommendation Systems

Focus-Driven Contrastive Learniang for Medical Question Summarization

1 code implementation1 Sep 2022 Ming Zhang, Shuai Dou, Ziyang Wang, Yunfang Wu

Automatic medical question summarization can significantly help the system to understand consumer health questions and retrieve correct answers.

Contrastive Learning

Taxonomy and evolution predicting using deep learning in images

1 code implementation28 Jun 2022 Jiewen Xiao, Wenbin Liao, Ming Zhang, Jing Wang, Jianxin Wang, Yihua Yang

Molecular and morphological characters, as important parts of biological taxonomy, are contradictory but need to be integrated.

Fine-Grained Image Recognition Zero-Shot Learning

A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs

2 code implementations7 Jun 2022 Zhaocheng Zhu, Xinyu Yuan, Mikhail Galkin, Sophie Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang

Experiments on both transductive and inductive knowledge graph reasoning benchmarks show that A*Net achieves competitive performance with existing state-of-the-art path-based methods, while merely visiting 10% nodes and 10% edges at each iteration.

Knowledge Graphs

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

no code implementations21 May 2022 Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang

This problem is typically solved by using graph neural networks (GNNs), which yet rely on a large number of labeled graphs for training and are unable to leverage unlabeled graphs.

Graph Classification

End-to-End Rubbing Restoration Using Generative Adversarial Networks

1 code implementation8 May 2022 Gongbo Sun, Zijie Zheng, Ming Zhang

Specifically, we collect characters from the Zhang Menglong Bei and build up the first rubbing restoration dataset.

A Probabilistic Model-Based Robust Waveform Design for MIMO Radar Detection

no code implementations9 Apr 2022 Xuyang Wang, Bo Tang, Ming Zhang

This paper addresses robust waveform design for multiple-input-multiple-output (MIMO) radar detection.

Orthonormal Product Quantization Network for Scalable Face Image Retrieval

1 code implementation1 Jul 2021 Ming Zhang, Xuefei Zhe, Hong Yan

Experiments are conducted on four commonly-used face datasets under both seen and unseen identities retrieval settings.

Face Image Retrieval Informativeness +2

DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation

1 code implementation21 Jun 2021 Yifan Wang, Suyao Tang, Yuntong Lei, Weiping Song, Sheng Wang, Ming Zhang

In this paper, we propose a novel disentangled heterogeneous graph attention network DisenHAN for top-$N$ recommendation, which learns disentangled user/item representations from different aspects in a heterogeneous information network.

Collaborative Filtering Graph Attention +1

Partial Feature Selection and Alignment for Multi-Source Domain Adaptation

no code implementations CVPR 2021 Yangye Fu, Ming Zhang, Xing Xu, Zuo Cao, Chao Ma, Yanli Ji, Kai Zuo, Huimin Lu

By assuming that the source and target domains share consistent key feature representations and identical label space, existing studies on MSDA typically utilize the entire union set of features from both the source and target domains to obtain the feature map and align the map for each category and domain.

feature selection Partial Domain Adaptation

RangeIoUDet: Range Image Based Real-Time 3D Object Detector Optimized by Intersection Over Union

no code implementations CVPR 2021 Zhidong Liang, Zehan Zhang, Ming Zhang, Xian Zhao, ShiLiang Pu

Benefiting from the dense representation of the range image, RangeIoUDet is entirely constructed based on 2D convolution, making it possible to have a fast inference speed.

3D Object Detection Autonomous Driving +2

FNAS: Uncertainty-Aware Fast Neural Architecture Search

no code implementations25 May 2021 Jihao Liu, Ming Zhang, Yangting Sun, Boxiao Liu, Guanglu Song, Yu Liu, Hongsheng Li

Further, an architecture knowledge pool together with a block similarity function is proposed to utilize parameter knowledge and reduces the searching time by 2 times.

Fairness Neural Architecture Search +1

Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation

1 code implementation25 May 2021 Xiao Luo, Daqing Wu, Yiyang Gu, Chong Chen, Luchen Liu, Jinwen Ma, Ming Zhang, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua

Besides, CHCF integrates criterion learning and user preference learning into a unified framework, which can be trained jointly for the interaction prediction of the target behavior.

Collaborative Filtering Metric Learning +1

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

no code implementations26 Mar 2021 Ming Zhang, Mingming Zhang, Yiming Chen, Mingyang Li

In this work, we propose a novel method for performing inertial aided navigation, by using deep neural networks (DNNs).

Sensor Fusion

Improved Deep Classwise Hashing With Centers Similarity Learning for Image Retrieval

no code implementations17 Mar 2021 Ming Zhang, Hong Yan

Recently, deep classwise hashing introduced a classwise loss supervised by class labels information alternatively; however, we find it still has its drawback.

Image Retrieval Retrieval

Topologically protected valley-dependent quantum photonic circuits

no code implementations11 Mar 2021 Yang Chen, Xin-Tao He, Yu-Jie Cheng, Hao-Yang Qiu, Lan-Tian Feng, Ming Zhang, Dao-Xin Dai, Guang-Can Guo, Jian-Wen Dong, Xi-Feng Ren

Topological photonics has been introduced as a powerful platform for integrated optics, since it can deal with robust light transport, and be further extended to the quantum world.

Quantum Physics Optics

Time-dependent Clearance of Cyclosporine in Adult Renal Transplant Recipients: A Population Pharmacokinetic Perspective

no code implementations2 Mar 2021 Junjun Mao, Xiaoyan Qiu, Weiwei Qin, Luyang Xu, Ming Zhang, Mingkang Zhong

The CL/F of the non-CGC haplotype carrier was 14. 4% lower than that of the CGC haplotype carrier at 3 months post operation.

$P-V$ criticality and Joule-Thomson Expansion of Hayward-AdS black holes in 4D Einstein-Gauss-Bonnet gravity

no code implementations8 Feb 2021 Ming Zhang, Chao-Ming Zhang, De-Cheng Zou, Rui-Hong Yue

In this paper, the $P-V$ criticality and Joule-Thomson Expansion of Hayward-AdS black holes in 4D Einstein-Gauss-Bonnet gravity are studied in the extended phase space.

Action Detection High Energy Physics - Theory

MoDL-QSM: Model-based Deep Learning for Quantitative Susceptibility Mapping

1 code implementation21 Jan 2021 Ruimin Feng, Jiayi Zhao, He Wang, Baofeng Yang, Jie Feng, Yuting Shi, Ming Zhang, Chunlei Liu, Yuyao Zhang, Jie Zhuang, Hongjiang Wei

However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label.


Fast MNAS: Uncertainty-aware Neural Architecture Search with Lifelong Learning

no code implementations1 Jan 2021 Jihao Liu, Yangting Sun, Ming Zhang, Boxiao Liu, Yu Liu

Further, a life-long knowledge pool together with a block similarity function is proposed to utilize the lifelong parameter knowledge and reduces the searching time by 2 times.

Fairness Neural Architecture Search

Tomographic imaging of complete quantum state of matter by ultrafast diffraction

no code implementations22 Dec 2020 Ming Zhang, Shuqiao Zhang, Haitan Xu, Hankai Zhang, Xiangxu Mu, R. J. Dwayne Miller, Anatoly Ischenko, Oriol Vendrell, Zheng Li

With the ability to directly obtain the Wigner function and density matrix of photon states, quantum tomography (QT) has had a significant impact on quantum optics, quantum computing and quantum information.

Quantum Physics

Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction

no code implementations14 Dec 2020 Jiafa He, Chengwei Pan, Can Yang, Ming Zhang, Yang Wang, Xiaowei Zhou, Yizhou Yu

The main idea is to use CNNs to learn local appearances of vessels in image crops while using another point-cloud network to learn the global geometry of vessels in the entire image.

Representation Learning

$K$-theoretic quasimap wall-crossing

no code implementations2 Dec 2020 Ming Zhang, Yang Zhou

In this paper, we prove a K-theoretic wall-crossing formula for $\epsilon$-stable quasimaps for all GIT targets in all genera.

Algebraic Geometry Mathematical Physics Mathematical Physics 14N35

Multi-agent Trajectory Prediction with Fuzzy Query Attention

1 code implementation NeurIPS 2020 Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu

Trajectory prediction for scenes with multiple agents and entities is a challenging problem in numerous domains such as traffic prediction, pedestrian tracking and path planning.

Decision Making Traffic Prediction +1

Partial FC: Training 10 Million Identities on a Single Machine

6 code implementations11 Oct 2020 Xiang An, Xuhan Zhu, Yang Xiao, Lan Wu, Ming Zhang, Yuan Gao, Bin Qin, Debing Zhang, Ying Fu

The experiment demonstrates no loss of accuracy when training with only 10\% randomly sampled classes for the softmax-based loss functions, compared with training with full classes using state-of-the-art models on mainstream benchmarks.

Face Identification Face Recognition +2

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

no code implementations9 Oct 2020 Yicheng Wu, Chengwei Pan, Shuqi Wang, Ming Zhang, Yong Xia, Yizhou Yu

Analyzing the morphological attributes of blood vessels plays a critical role in the computer-aided diagnosis of many cardiovascular and ophthalmologic diseases.

MAFF-Net: Filter False Positive for 3D Vehicle Detection with Multi-modal Adaptive Feature Fusion

no code implementations23 Sep 2020 Zehan Zhang, Ming Zhang, Zhidong Liang, Xian Zhao, Ming Yang, Wenming Tan, ShiLiang Pu

Experimental results on the KITTI dataset demonstrate significant improvement in filtering false positive over the approach using only point cloud data.

Autonomous Driving

New gedanken experiment on higher-dimensional asymptotically AdS Reissner-Nordström black hole

no code implementations16 Sep 2020 Ming Zhang, Jie Jiang

Viewing the negative cosmological constant as a dynamical quantity derived from the matter field, we study the weak cosmic censorship conjecture for the higher-dimensional asymptotically AdS Reissner-Nordstr\"om black hole.

General Relativity and Quantum Cosmology High Energy Physics - Theory

Snowmass 2021 LoI: Determination of cosmic ray properties in the local interstellar medium with all-sky anisotropy observations

no code implementations10 Sep 2020 Paolo Desiati, Juan Carlos Díaz Vélez, Nikolai Pogorelov, Ming Zhang

Propagation of Galactic cosmic rays (CR) in the interstellar medium (ISM) is among the unsolved problems in particle astrophysics.

High Energy Astrophysical Phenomena

Augmented Bi-path Network for Few-shot Learning

no code implementations15 Jul 2020 Baoming Yan, Chen Zhou, Bo Zhao, Kan Guo, Jiang Yang, Xiaobo Li, Ming Zhang, Yizhou Wang

Finally, the model learns to compare global and local features separately, i. e., in two paths, before merging the similarities.

Few-Shot Learning

EasyQuant: Post-training Quantization via Scale Optimization

1 code implementation30 Jun 2020 Di Wu, Qi Tang, Yongle Zhao, Ming Zhang, Ying Fu, Debing Zhang

The 8 bits quantization has been widely applied to accelerate network inference in various deep learning applications.


Wasserstein Distance guided Adversarial Imitation Learning with Reward Shape Exploration

1 code implementation5 Jun 2020 Ming Zhang, Yawei Wang, Xiaoteng Ma, Li Xia, Jun Yang, Zhiheng Li, Xiu Li

The generative adversarial imitation learning (GAIL) has provided an adversarial learning framework for imitating expert policy from demonstrations in high-dimensional continuous tasks.

Continuous Control Imitation Learning

When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications

no code implementations24 May 2020 Zequn Liu, Ruiyi Zhang, Yiping Song, Ming Zhang

Model-Agnostic Meta-Learning (MAML), a model-agnostic meta-learning method, is successfully employed in NLP applications including few-shot text classification and multi-domain low-resource language generation.

Few-Shot Text Classification Language Modelling +4

Learning to Answer Ambiguous Questions with Knowledge Graph

no code implementations25 Dec 2019 Yikai Zhu, Jianhao Shen, Ming Zhang

In the task of factoid question answering over knowledge base, many questions have more than one plausible interpretation.

Question Answering

Predictive Multi-level Patient Representations from Electronic Health Records

no code implementations12 Nov 2019 Zichang Wang, Haoran Li, Lu-chen Liu, Haoxian Wu, Ming Zhang

Most related studies transform EHR data of a patient into a sequence of clinical events in temporal order and then use sequential models to learn patient representations for outcome prediction.

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

no code implementations COLING 2020 Yichun Yin, Chenguang Wang, Ming Zhang

Dependency context-based word embedding jointly learns the representations of word and dependency context, and has been proved effective in aspect term extraction.

Aspect Term Extraction and Sentiment Classification POS +1

Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks

1 code implementation ACL 2020 Yiping Song, Zequn Liu, Wei Bi, Rui Yan, Ming Zhang

Training the generative models with minimal corpus is one of the critical challenges for building open-domain dialogue systems.

Dialogue Generation Language Modelling +1

Early Prediction of Sepsis From Clinical Datavia Heterogeneous Event Aggregation

no code implementations14 Oct 2019 Lu-chen Liu, Haoxian Wu, Zichang Wang, Zequn Liu, Ming Zhang

Rather than directly applying the LSTM model to the event sequences, our proposed model firstly aggregates heterogeneous clinical events in a short period and then captures temporal interactions of the aggregated representations with LSTM.


no code implementations25 Sep 2019 Kewei Cheng, Yikai Zhu, Ming Zhang, Yizhou Sun

Knowledge graph has gained increasing attention in recent years for its successful applications of numerous tasks.

Knowledge Graph Embedding

Neural Correction Model for Open-Domain Named Entity Recognition

1 code implementation13 Sep 2019 Mengdi Zhu, Zheye Deng, Wenhan Xiong, Mo Yu, Ming Zhang, William Yang Wang

In this work, to address the low precision and recall problems, we first utilize DBpedia as the source of distant supervision to annotate abstracts from Wikipedia and design a neural correction model trained with a human-annotated NER dataset, DocRED, to correct the false entity labels.

Multi-Task Learning named-entity-recognition +4

Ekar: An Explainable Method for Knowledge Aware Recommendation

2 code implementations22 Jun 2019 Weiping Song, Zhijian Duan, Ziqing Yang, Hao Zhu, Ming Zhang, Jian Tang

Recently, a variety of methods have been developed for this problem, which generally try to learn effective representations of users and items and then match items to users according to their representations.

Knowledge-Aware Recommendation Knowledge Graphs +1

Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction

no code implementations20 Mar 2019 Lu-chen Liu, Haoran Li, Zhiting Hu, Haoran Shi, Zichang Wang, Jian Tang, Ming Zhang

Our model learns hierarchical representationsof event sequences, to adaptively distinguish between short-range and long-range events, and accurately capture coretemporal dependencies.

Session-based Social Recommendation via Dynamic Graph Attention Networks

2 code implementations25 Feb 2019 Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang

However, recommendation in online communities is a challenging problem: 1) users' interests are dynamic, and 2) users are influenced by their friends.

 Ranked #1 on Recommendation Systems on Douban (NDCG metric)

Graph Attention Recommendation Systems

Combating Fake News: A Survey on Identification and Mitigation Techniques

no code implementations18 Jan 2019 Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu

The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news, and mitigation of its widespread impact on public opinion.


Efficient Spiking Neural Networks with Logarithmic Temporal Coding

no code implementations10 Nov 2018 Ming Zhang, Nenggan Zheng, De Ma, Gang Pan, Zonghua Gu

A Spiking Neural Network (SNN) can be trained indirectly by first training an Artificial Neural Network (ANN) with the conventional backpropagation algorithm, then converting it into an SNN.

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

13 code implementations29 Oct 2018 Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, Jian Tang

Afterwards, a multi-head self-attentive neural network with residual connections is proposed to explicitly model the feature interactions in the low-dimensional space.

Click-Through Rate Prediction Recommendation Systems

Towards WARSHIP: Combining Components of Brain-Inspired Computing of RSH for Image Super Resolution

no code implementations3 Oct 2018 Wendi Xu, Ming Zhang

Evolution of deep learning shows that some algorithmic tricks are more durable , while others are not.

Image Super-Resolution

Theory of Generative Deep Learning : Probe Landscape of Empirical Error via Norm Based Capacity Control

no code implementations3 Oct 2018 Wendi Xu, Ming Zhang

Despite its remarkable empirical success as a highly competitive branch of artificial intelligence, deep learning is often blamed for its widely known low interpretation and lack of firm and rigorous mathematical foundation.

Image Super-Resolution

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

1 code implementation13 Mar 2018 Lu-chen Liu, Jianhao Shen, Ming Zhang, Zichang Wang, Jian Tang

One important application is clinical endpoint prediction, which aims to predict whether a disease, a symptom or an abnormal lab test will happen in the future according to patients' history records.

Towards Automated ICD Coding Using Deep Learning

no code implementations11 Nov 2017 Haoran Shi, Pengtao Xie, Zhiting Hu, Ming Zhang, Eric P. Xing

Considering the complicated and dedicated process to assign correct codes to each patient admission based on overall diagnosis, we propose a hierarchical deep learning model with attention mechanism which can automatically assign ICD diagnostic codes given written diagnosis.

General Classification Management

Diversifying Neural Conversation Model with Maximal Marginal Relevance

no code implementations IJCNLP 2017 Yiping Song, Zhiliang Tian, Dongyan Zhao, Ming Zhang, Rui Yan

However, traditional seq2seq suffer from a severe weakness: during beam search decoding, they tend to rank universal replies at the top of the candidate list, resulting in the lack of diversity among candidate replies.

Document Summarization Information Retrieval +1

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

1 code implementation19 Sep 2017 Meng Qu, Jian Tang, Jingbo Shang, Xiang Ren, Ming Zhang, Jiawei Han

Existing approaches usually study networks with a single type of proximity between nodes, which defines a single view of a network.

Representation Learning

Syntax Aware LSTM model for Semantic Role Labeling

no code implementations WS 2017 Feng Qian, Lei Sha, Baobao Chang, Lu-chen Liu, Ming Zhang

In Semantic Role Labeling (SRL) task, the tree structured dependency relation is rich in syntax information, but it is not well handled by existing models.

Feature Engineering Machine Translation +2

Syntax Aware LSTM Model for Chinese Semantic Role Labeling

no code implementations3 Apr 2017 Feng Qian, Lei Sha, Baobao Chang, Lu-chen Liu, Ming Zhang

As for semantic role labeling (SRL) task, when it comes to utilizing parsing information, both traditional methods and recent recurrent neural network (RNN) based methods use the feature engineering way.

Chinese Semantic Role Labeling Dependency Parsing +2

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

no code implementations2 Jan 2017 Wenjia Meng, Zonghua Gu, Ming Zhang, Zhaohui Wu

With the rapid proliferation of Internet of Things and intelligent edge devices, there is an increasing need for implementing machine learning algorithms, including deep learning, on resource-constrained mobile embedded devices with limited memory and computation power.

General Classification Model Compression +1

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

no code implementations29 Nov 2016 Jian Tang, Cheng Li, Ming Zhang, Qiaozhu Mei

With this reinforced random walk as a general process embedded in classical topic models, we obtain \textit{diverse topic models} that are able to extract the most prominent and diverse topics from data.

Data Summarization Topic Models

Context-aware Natural Language Generation with Recurrent Neural Networks

1 code implementation29 Nov 2016 Jian Tang, Yifan Yang, Sam Carton, Ming Zhang, Qiaozhu Mei

This paper studied generating natural languages at particular contexts or situations.

Text Generation

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

2 code implementations23 Oct 2016 Yiping Song, Rui Yan, Xiang Li, Dongyan Zhao, Ming Zhang

In this paper, we propose a novel ensemble of retrieval-based and generation-based dialog systems in the open domain.


Dialogue Session Segmentation by Embedding-Enhanced TextTiling

no code implementations13 Oct 2016 Yiping Song, Lili Mou, Rui Yan, Li Yi, Zinan Zhu, Xiaohua Hu, Ming Zhang

In human-computer conversation systems, the context of a user-issued utterance is particularly important because it provides useful background information of the conversation.

Word Embeddings

Improving Color Constancy by Discounting the Variation of Camera Spectral Sensitivity

no code implementations6 Sep 2016 Shao-Bing Gao, Ming Zhang, Chao-Yi Li, Yong-Jie Li

Most color constancy (CC) models have been designed to first estimate the illuminant color, which is then removed from the color biased image to obtain an image taken under white light, without the explicit consideration of CSS effect on CC.

Color Constancy

World Knowledge as Indirect Supervision for Document Clustering

no code implementations30 Jul 2016 Chenguang Wang, Yangqiu Song, Dan Roth, Ming Zhang, Jiawei Han

We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network.


Unsupervised Word and Dependency Path Embeddings for Aspect Term Extraction

no code implementations25 May 2016 Yichun Yin, Furu Wei, Li Dong, Kaimeng Xu, Ming Zhang, Ming Zhou

In this paper, we develop a novel approach to aspect term extraction based on unsupervised learning of distributed representations of words and dependency paths.

Term Extraction

StalemateBreaker: A Proactive Content-Introducing Approach to Automatic Human-Computer Conversation

no code implementations15 Apr 2016 Xiang Li, Lili Mou, Rui Yan, Ming Zhang

In this paper, we propose StalemateBreaker, a conversation system that can proactively introduce new content when appropriate.

Visualizing Large-scale and High-dimensional Data

5 code implementations1 Feb 2016 Jian Tang, Jingzhou Liu, Ming Zhang, Qiaozhu Mei

We propose the LargeVis, a technique that first constructs an accurately approximated K-nearest neighbor graph from the data and then layouts the graph in the low-dimensional space.

graph construction Vocal Bursts Intensity Prediction

LINE: Large-scale Information Network Embedding

8 code implementations12 Mar 2015 Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, Qiaozhu Mei

This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful in many tasks such as visualization, node classification, and link prediction.

Graph Embedding Link Prediction +2

"Look Ma, No Hands!" A Parameter-Free Topic Model

no code implementations10 Sep 2014 Jian Tang, Ming Zhang, Qiaozhu Mei

We show that the new parameter can be further eliminated by two parameter-free treatments: either by monitoring the diversity among the discovered topics or by a weak supervision from users in the form of an exemplar topic.

Model Selection Topic Models

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