b'Xinwang Liu'

research

∙ 03/14/2023

GANN: Graph Alignment Neural Network for Semi-Supervised Learning

Graph neural networks (GNNs) have been widely investigated in the field ...

0 Linxuan Song, et al. ∙

research

∙ 02/15/2023

Revisiting Initializing Then Refining: An Incomplete and Missing Graph Imputation Network

With the development of various applications, such as social networks an...

0 Wenxuan Tu, et al. ∙

research

∙ 01/03/2023

Cluster-guided Contrastive Graph Clustering Network

Benefiting from the intrinsic supervision information exploitation capab...

0 Xihong Yang, et al. ∙

research

∙ 12/16/2022

Hard Sample Aware Network for Contrastive Deep Graph Clustering

Contrastive deep graph clustering, which aims to divide nodes into disjo...

0 Yue Liu, et al. ∙

research

∙ 12/07/2022

Contrastive Deep Graph Clustering with Learnable Augmentation

Graph contrastive learning is an important method for deep graph cluster...

0 Xihong Yang, et al. ∙

research

∙ 11/19/2022

Relational Symmetry based Knowledge Graph Contrastive Learning

Knowledge graph embedding (KGE) aims to learn powerful representations t...

0 Ke Liang, et al. ∙

research

∙ 08/02/2022

Late Fusion Multi-view Clustering via Global and Local Alignment Maximization

Multi-view clustering (MVC) optimally integrates complementary informati...

0 Siwei Wang, et al. ∙

research

∙ 07/13/2022

Multiple Kernel Clustering with Dual Noise Minimization

Clustering is a representative unsupervised method widely applied in mul...

33 Junpu Zhang, et al. ∙

research

∙ 07/05/2022

Local Sample-weighted Multiple Kernel Clustering with Consensus Discriminative Graph

Multiple kernel clustering (MKC) is committed to achieving optimal infor...

0 Liang Li, et al. ∙

research

∙ 06/06/2022

Interpolation-based Correlation Reduction Network for Semi-Supervised Graph Learning

Graph Neural Networks (GNNs) have achieved promising performance in semi...

11 Xihong Yang, et al. ∙

research

∙ 05/30/2022

Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching Correspondences

Multi-view anchor graph clustering selects representative anchors to avo...

0 Siwei Wang, et al. ∙

research

∙ 05/11/2022

Simple Contrastive Graph Clustering

Contrastive learning has recently attracted plenty of attention in deep ...

6 Yue Liu, et al. ∙

research

∙ 03/02/2022

DisARM: Displacement Aware Relation Module for 3D Detection

We introduce Displacement Aware Relation Module (DisARM), a novel neural...

0 Yao Duan, et al. ∙

research

∙ 02/25/2022

Improved Dual Correlation Reduction Network

Deep graph clustering, which aims to reveal the underlying graph structu...

2 Yue Liu, et al. ∙

research

∙ 02/24/2022

Interpolation-based Contrastive Learning for Few-Label Semi-Supervised Learning

Semi-supervised learning (SSL) has long been proved to be an effective t...

0 Xihong Yang, et al. ∙

research

∙ 12/29/2021

Deep Graph Clustering via Dual Correlation Reduction

Deep graph clustering, which aims to reveal the underlying graph structu...

12 Yue Liu, et al. ∙

research

∙ 12/09/2021

Siamese Attribute-missing Graph Auto-encoder

Graph representation learning (GRL) on attribute-missing graphs, which i...

6 Wenxuan Tu, et al. ∙

research

∙ 08/05/2021

Video Abnormal Event Detection by Learning to Complete Visual Cloze Tests

Video abnormal event detection (VAD) is a vital semi-supervised task tha...

13 Siqi Wang, et al. ∙

research

∙ 08/04/2021

Sensing Anomalies like Humans: A Hominine Framework to Detect Abnormal Events from Unlabeled Videos

Video anomaly detection (VAD) has constantly been a vital topic in video...

0 Siqi Wang, et al. ∙

research

∙ 05/01/2021

Multi-view Clustering via Deep Matrix Factorization and Partition Alignment

Multi-view clustering (MVC) has been extensively studied to collect mult...

0 Chen Zhang, et al. ∙

research

∙ 05/01/2021

Multi-view Clustering with Deep Matrix Factorization and Global Graph Refinement

Multi-view clustering is an important yet challenging task in machine le...

7 Chen Zhang, et al. ∙

research

∙ 04/27/2021

Multi-view Deep One-class Classification: A Systematic Exploration

One-class classification (OCC), which models one single positive class a...

0 Siqi Wang, et al. ∙

research

∙ 03/21/2021

Deep Distribution-preserving Incomplete Clustering with Optimal Transport

Clustering is a fundamental task in the computer vision and machine lear...

10 Mingjie Luo, et al. ∙

research

∙ 03/10/2021

A Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks

Real-world data usually have high dimensionality and it is important to ...

0 Xiang Wang, et al. ∙

research

∙ 12/15/2020

Deep Fusion Clustering Network

Deep clustering is a fundamental yet challenging task for data analysis....

0 Wenxuan Tu, et al. ∙

research

∙ 09/09/2020

Meta-learning for Multi-variable Non-convex Optimization Problems: Iterating Non-optimums Makes Optimum Possible

In this paper, we aim to address the problem of solving a non-convex opt...

0 Jingyuan Xia, et al. ∙

research

∙ 09/05/2020

A Self-Supervised Gait Encoding Approach with Locality-Awareness for 3D Skeleton Based Person Re-Identification

Person re-identification (Re-ID) via gait features within 3D skeleton se...

9 Haocong Rao, et al. ∙

research

∙ 08/31/2020

Multi-View Spectral Clustering with High-Order Optimal Neighborhood Laplacian Matrix

Multi-view spectral clustering can effectively reveal the intrinsic clus...

0 Weixuan Liang, et al. ∙

research

∙ 08/31/2020

Structured Graph Learning for Clustering and Semi-supervised Classification

Graphs have become increasingly popular in modeling structures and inter...

4 Zhao Kang, et al. ∙

research

∙ 07/13/2020

Embedded Deep Bilinear Interactive Information and Selective Fusion for Multi-view Learning

As a concrete application of multi-view learning, multi-view classificat...

0 Jinglin Xu, et al. ∙

research

∙ 05/11/2020

SimpleMKKM: Simple Multiple Kernel K-means

We propose a simple yet effective multiple kernel clustering algorithm, ...

0 Xinwang Liu, et al. ∙

research

∙ 03/09/2020

Nearly Optimal Risk Bounds for Kernel K-Means

In this paper, we study the statistical properties of the kernel k-means...

19 Yong Liu, et al. ∙

research

∙ 02/20/2020

Differentially Private ERM Based on Data Perturbation

In this paper, after observing that different training data instances af...

7 Yilin Kang, et al. ∙

research

∙ 01/15/2020

Outlier Detection Ensemble with Embedded Feature Selection

Feature selection places an important role in improving the performance ...

0 Li Cheng, et al. ∙

research

∙ 11/28/2019

Understand Dynamic Regret with Switching Cost for Online Decision Making

As a metric to measure the performance of an online method, dynamic regr...

0 Yawei Zhao, et al. ∙

research

∙ 08/04/2019

Simultaneous Clustering and Optimization for Evolving Datasets

Simultaneous clustering and optimization (SCO) has recently drawn much a...

7 Yawei Zhao, et al. ∙

research

∙ 12/26/2018

Dynamic Online Gradient Descent with Improved Query Complexity: A Theoretical Revisit

We provide a new theoretical analysis framework to investigate online gr...

0 Yawei Zhao, et al. ∙

research

∙ 09/06/2018

Deep Learning for Generic Object Detection: A Survey

Generic object detection, aiming at locating object instances from a lar...

0 Li Liu, et al. ∙

research

∙ 08/20/2018

Triangle Lasso for Simultaneous Clustering and Optimization in Graph Datasets

Recently, network lasso has drawn many attentions due to its remarkable ...

0 Yawei Zhao, et al. ∙

research

∙ 12/28/2017

Game-Theoretic Design of Optimal Two-Sided Rating Protocols for Service Exchange Dilemma in Crowdsourcing

Despite the increasing popularity and successful examples of crowdsourci...

0 Jianfeng Lu, et al. ∙

research

∙ 11/11/2017

DeepKSPD: Learning Kernel-matrix-based SPD Representation for Fine-grained Image Recognition

Being symmetric positive-definite (SPD), covariance matrix has tradition...

0 Melih Engin, et al. ∙

research

∙ 09/07/2014

A Computational Model of the Short-Cut Rule for 2D Shape Decomposition

We propose a new 2D shape decomposition method based on the short-cut ru...

0 Lei Luo, et al. ∙

Xinwang Liu

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