b'Zhao Kang'

research

∙ 06/24/2023

Intensity-free Convolutional Temporal Point Process: Incorporating Local and Global Event Contexts

Event prediction in the continuous-time domain is a crucial but rather d...

0 Wang-Tao Zhou, et al. ∙

research

∙ 05/03/2023

Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering

Graph neural networks (GNNs) based methods have achieved impressive perf...

0 Erlin Pan, et al. ∙

research

∙ 04/19/2023

TieFake: Title-Text Similarity and Emotion-Aware Fake News Detection

Fake news detection aims to detect fake news widely spreading on social ...

0 Quanjiang Guo, et al. ∙

research

∙ 03/07/2023

Document-level Relation Extraction with Cross-sentence Reasoning Graph

Relation extraction (RE) has recently moved from the sentence-level to d...

0 Hongfei Liu, et al. ∙

research

∙ 09/22/2022

High-order Multi-view Clustering for Generic Data

Graph-based multi-view clustering has achieved better performance than m...

0 Erlin Pan, et al. ∙

research

∙ 09/02/2022

Structure-Preserving Graph Representation Learning

Though graph representation learning (GRL) has made significant progress...

0 Ruiyi Fang, et al. ∙

research

∙ 07/13/2022

Eliminating Gradient Conflict in Reference-based Line-art Colorization

Reference-based line-art colorization is a challenging task in computer ...

11 Zekun Li, et al. ∙

research

∙ 04/22/2022

Log-based Sparse Nonnegative Matrix Factorization for Data Representation

Nonnegative matrix factorization (NMF) has been widely studied in recent...

0 Chong Peng, et al. ∙

research

∙ 10/22/2021

Multi-view Contrastive Graph Clustering

With the explosive growth of information technology, multi-view graph da...

0 Erlin Pan, et al. ∙

research

∙ 08/10/2021

Self-supervised Consensus Representation Learning for Attributed Graph

Attempting to fully exploit the rich information of topological structur...

0 Changshu Liu, et al. ∙

research

∙ 06/25/2021

Self-paced Principal Component Analysis

Principal Component Analysis (PCA) has been widely used for dimensionali...

39 Zhao Kang, et al. ∙

research

∙ 06/18/2021

Towards Clustering-friendly Representations: Subspace Clustering via Graph Filtering

Finding a suitable data representation for a specific task has been show...

0 Zhengrui Ma, et al. ∙

research

∙ 04/08/2021

Pseudo-supervised Deep Subspace Clustering

Auto-Encoder (AE)-based deep subspace clustering (DSC) methods have achi...

0 Juncheng Lv, et al. ∙

research

∙ 02/16/2021

Structured Graph Learning for Scalable Subspace Clustering: From Single-view to Multi-view

Graph-based subspace clustering methods have exhibited promising perform...

0 Zhao Kang, et al. ∙

research

∙ 11/03/2020

Kernel Two-Dimensional Ridge Regression for Subspace Clustering

Subspace clustering methods have been widely studied recently. When the ...

7 Chong Peng, 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

∙ 07/11/2020

Relation-Guided Representation Learning

Deep auto-encoders (DAEs) have achieved great success in learning data r...

5 Zhao Kang, et al. ∙

research

∙ 05/19/2020

Two-Dimensional Semi-Nonnegative Matrix Factorization for Clustering

In this paper, we propose a new Semi-Nonnegative Matrix Factorization me...

0 Chong Peng, et al. ∙

research

∙ 12/03/2019

Multi-view Subspace Clustering via Partition Fusion

Multi-view clustering is an important approach to analyze multi-view dat...

2 Juncheng Lv, et al. ∙

research

∙ 12/03/2019

Structure Learning with Similarity Preserving

Leveraging on the underlying low-dimensional structure of data, low-rank...

13 Zhao Kang, et al. ∙

research

∙ 11/21/2019

Large-scale Multi-view Subspace Clustering in Linear Time

A plethora of multi-view subspace clustering (MVSC) methods have been pr...

16 Zhao Kang, et al. ∙

research

∙ 09/16/2019

Multi-graph Fusion for Multi-view Spectral Clustering

A panoply of multi-view clustering algorithms has been developed to deal...

5 Zhao Kang, et al. ∙

research

∙ 09/13/2019

Multiple Partitions Aligned Clustering

Multi-view clustering is an important yet challenging task due to the di...

3 Zhao Kang, et al. ∙

research

∙ 09/09/2019

Latent Multi-view Semi-Supervised Classification

To explore underlying complementary information from multiple views, in ...

0 Xiaofan Bo, et al. ∙

research

∙ 07/09/2019

Nonnegative Matrix Factorization with Local Similarity Learning

Existing nonnegative matrix factorization methods focus on learning glob...

0 Chong Peng, et al. ∙

research

∙ 05/21/2019

Clustering with Similarity Preserving

Graph-based clustering has shown promising performance in many tasks. A ...

12 Zhao Kang, et al. ∙

research

∙ 04/16/2019

RES-PCA: A Scalable Approach to Recovering Low-rank Matrices

Robust principal component analysis (RPCA) has drawn significant attenti...

0 Chong Peng, et al. ∙

research

∙ 03/14/2019

Low-rank Kernel Learning for Graph-based Clustering

Constructing the adjacency graph is fundamental to graph-based clusterin...

14 Zhao Kang, et al. ∙

research

∙ 03/11/2019

Similarity Learning via Kernel Preserving Embedding

Data similarity is a key concept in many data-driven applications. Many ...

8 Zhao Kang, et al. ∙

research

∙ 12/17/2018

Robust Graph Learning from Noisy Data

Learning graphs from data automatically has shown encouraging performanc...

4 Zhao Kang, et al. ∙

research

∙ 06/20/2018

Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification

Multiple kernel learning (MKL) method is generally believed to perform b...

0 Zhao Kang, et al. ∙

research

∙ 11/16/2017

Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs

Generating high fidelity identity-preserving faces has a wide range of a...

0 Dan Ma, et al. ∙

research

∙ 11/12/2017

Unified Spectral Clustering with Optimal Graph

Spectral clustering has found extensive use in many areas. Most traditio...

0 Zhao Kang, et al. ∙

research

∙ 05/01/2017

Twin Learning for Similarity and Clustering: A Unified Kernel Approach

Many similarity-based clustering methods work in two separate steps incl...

0 Zhao Kang, et al. ∙

research

∙ 09/27/2016

A Fast Factorization-based Approach to Robust PCA

Robust principal component analysis (RPCA) has been widely used for reco...

0 Chong Peng, et al. ∙

research

∙ 09/27/2016

Top-N Recommendation on Graphs

Recommender systems play an increasingly important role in online applic...

0 Zhao Kang, et al. ∙

research

∙ 02/25/2016

Top-N Recommendation with Novel Rank Approximation

The importance of accurate recommender systems has been widely recognize...

0 Zhao Kang, et al. ∙

research

∙ 01/19/2016

Top-N Recommender System via Matrix Completion

Top-N recommender systems have been investigated widely both in industry...

0 Zhao Kang, et al. ∙

research

∙ 11/17/2015

Robust PCA via Nonconvex Rank Approximation

Numerous applications in data mining and machine learning require recove...

0 Zhao Kang, et al. ∙

research

∙ 10/30/2015

Robust Subspace Clustering via Tighter Rank Approximation

Matrix rank minimization problem is in general NP-hard. The nuclear norm...

0 Zhao Kang, et al. ∙

research

∙ 08/18/2015

Robust Subspace Clustering via Smoothed Rank Approximation

Matrix rank minimizing subject to affine constraints arises in many appl...

0 Zhao Kang, et al. ∙

research

∙ 07/03/2015

LogDet Rank Minimization with Application to Subspace Clustering

Low-rank matrix is desired in many machine learning and computer vision ...

0 Zhao Kang, et al. ∙

Zhao Kang

Featured Co-authors