Search Results for author: Jian-Xin Li

Found 20 papers, 11 papers with code

Pairwise Learning for Name Disambiguation in Large-Scale Heterogeneous Academic Networks

no code implementations30 Aug 2020 Qingyun Sun, Hao Peng, Jian-Xin Li, Senzhang Wang, Xiangyu Dong, Liangxuan Zhao, Philip S. Yu, Lifang He

Although these attributes may change, an author's co-authors and research topics do not change frequently with time, which means that papers within a period have similar text and relation information in the academic network.

Graph Embedding

Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market

1 code implementation12 Aug 2020 Hao Peng, Jian-Xin Li, Zheng Wang, Renyu Yang, Mingzhe Liu, Mingming Zhang, Philip S. Yu, Lifang He

As a departure from prior work, Luce organizes the house data in a heterogeneous information network (HIN) where graph nodes are house entities and attributes that are important for house price valuation.

MODEL: Motif-based Deep Feature Learning for Link Prediction

no code implementations9 Aug 2020 Lei Wang, Jing Ren, Bo Xu, Jian-Xin Li, Wei Luo, Feng Xia

Link prediction plays an important role in network analysis and applications.

Link Prediction

Detecting Topic and Sentiment Dynamics Due to COVID-19 Pandemic Using Social Media

no code implementations5 Jul 2020 Hui Yin, Shuiqiao Yang, Jian-Xin Li

The large scale social media posts (e. g., tweets) provide an ideal data source to infer the mental health for people during this pandemic period.

Heuristic Semi-Supervised Learning for Graph Generation Inspired by Electoral College

1 code implementation10 Jun 2020 Chen Li, Xutan Peng, Hao Peng, Jian-Xin Li, Lihong Wang, Philip S. Yu, Lifang He

Recently, graph-based algorithms have drawn much attention because of their impressive success in semi-supervised setups.

Graph Attention Graph Generation

Interpretable and Efficient Heterogeneous Graph Convolutional Network

1 code implementation27 May 2020 Yaming Yang, Ziyu Guan, Jian-Xin Li, Wei Zhao, Jiangtao Cui, Quan Wang

However, regarding Heterogeneous Information Network (HIN), existing HIN-oriented GCN methods still suffer from two deficiencies: (1) they cannot flexibly explore all possible meta-paths and extract the most useful ones for a target object, which hinders both effectiveness and interpretability; (2) they often need to generate intermediate meta-path based dense graphs, which leads to high computational complexity.

Itinerant topological magnons in Haldane Hubbard model with a nearly-flat electron band

1 code implementation25 Aug 2019 Zhao-Long Gu, Zhao-Yang Dong, Shun-Li Yu, Jian-Xin Li

We find an exact set of bases for magnons in the flatband limit constructed from sublattice particle-hole vectors and derive an effective model to explore the origin of the topological magnon which is attributed to the ``mass inversion mechanism''.

Strongly Correlated Electrons

Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification

1 code implementation9 Jun 2019 Hao Peng, Jian-Xin Li, Qiran Gong, Senzhang Wang, Lifang He, Bo Li, Lihong Wang, Philip S. Yu

In this paper, we propose a novel hierarchical taxonomy-aware and attentional graph capsule recurrent CNNs framework for large-scale multi-label text classification.

General Classification Multi Label Text Classification +3

Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks

1 code implementation9 Jun 2019 Hao Peng, Jian-Xin Li, Qiran Gong, Yangqiu Song, Yuanxing Ning, Kunfeng Lai, Philip S. Yu

In this paper, we design an event meta-schema to characterize the semantic relatedness of social events and build an event-based heterogeneous information network (HIN) integrating information from external knowledge base, and propose a novel Pair-wise Popularity Graph Convolutional Network (PP-GCN) based fine-grained social event categorization model.

Clustering Event Detection

Dynamic Network Embedding via Incremental Skip-gram with Negative Sampling

1 code implementation9 Jun 2019 Hao Peng, Jian-Xin Li, Hao Yan, Qiran Gong, Senzhang Wang, Lin Liu, Lihong Wang, Xiang Ren

Most existing methods focus on learning the structural representations of vertices in a static network, but cannot guarantee an accurate and efficient embedding in a dynamic network scenario.

Link Prediction Multi-Label Classification +1

Graph Convolutional Neural Networks via Motif-based Attention

no code implementations11 Nov 2018 Hao Peng, Jian-Xin Li, Qiran Gong, Senzhang Wang, Yuanxing Ning, Philip S. Yu

Different from previous convolutional neural networks on graphs, we first design a motif-matching guided subgraph normalization method to capture neighborhood information.

General Classification Graph Classification

Ferromagnetism and spin excitations in topological Hubbard models with a flatband

2 code implementations29 Oct 2018 Xiao-Fei Su, Zhao-Long Gu, Zhao-Yang Dong, Shun-Li Yu, Jian-Xin Li

By using the numerical exact diagonalization method with a projection onto the nearly-flat band, we obtain the ferromagnetic spin-1 excitation spectra for both the Chern and $Z_2$ Hubbard models, consisting of spin waves and Stoner continuum.

Strongly Correlated Electrons

Benchmark data and method for real-time people counting in cluttered scenes using depth sensors

1 code implementation12 Apr 2018 Shi-Jie Sun, Naveed Akhtar, HuanSheng Song, Chaoyang Zhang, Jian-Xin Li, Ajmal Mian

A thorough evaluation on PCDS demonstrates that our technique is able to count people in cluttered scenes with high accuracy at 45 fps on a 1. 7 GHz processor, and hence it can be deployed for effective real-time people counting for intelligent transportation systems.


Topological Magnons in a One-dimensional Itinerant Flatband Ferromagnet

2 code implementations16 Jan 2018 Xiao-Fei Su, Zhao-Long Gu, Zhao-Yang Dong, Jian-Xin Li

Different from previous scenarios that topological magnons emerge in local spin models, we propose an alternative that itinerant electron magnets can host topological magnons.

Strongly Correlated Electrons

Stacked Kernel Network

no code implementations25 Nov 2017 Shuai Zhang, Jian-Xin Li, Pengtao Xie, Yingchun Zhang, Minglai Shao, Haoyi Zhou, Mengyi Yan

Similar to DNNs, a SKN is composed of multiple layers of hidden units, but each parameterized by a RKHS function rather than a finite-dimensional vector.

On the representation and embedding of knowledge bases beyond binary relations

no code implementations28 Apr 2016 Jianfeng Wen, Jian-Xin Li, Yongyi Mao, Shini Chen, Richong Zhang

The models developed to date for knowledge base embedding are all based on the assumption that the relations contained in knowledge bases are binary.

Quantum cluster approach to the topological invariants in correlated Chern insulators

no code implementations16 Dec 2015 Zhao-Long Gu, Kai Li, Jian-Xin Li

We detect the topological properties of Chern insulators with strong Coulomb interactions by use of cluster perturbation theory and variational cluster approach.

Strongly Correlated Electrons

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