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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...
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05/03/2023
Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering
Graph neural networks (GNNs) based methods have achieved impressive perf...
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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 ...
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03/07/2023
Document-level Relation Extraction with Cross-sentence Reasoning Graph
Relation extraction (RE) has recently moved from the sentence-level to d...
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09/22/2022
High-order Multi-view Clustering for Generic Data
Graph-based multi-view clustering has achieved better performance than m...
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09/02/2022
Structure-Preserving Graph Representation Learning
Though graph representation learning (GRL) has made significant progress...
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07/13/2022
Eliminating Gradient Conflict in Reference-based Line-art Colorization
Reference-based line-art colorization is a challenging task in computer ...
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04/22/2022
Log-based Sparse Nonnegative Matrix Factorization for Data Representation
Nonnegative matrix factorization (NMF) has been widely studied in recent...
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10/22/2021
Multi-view Contrastive Graph Clustering
With the explosive growth of information technology, multi-view graph da...
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08/10/2021
Self-supervised Consensus Representation Learning for Attributed Graph
Attempting to fully exploit the rich information of topological structur...
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06/25/2021
Self-paced Principal Component Analysis
Principal Component Analysis (PCA) has been widely used for dimensionali...
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06/18/2021
Towards Clustering-friendly Representations: Subspace Clustering via Graph Filtering
Finding a suitable data representation for a specific task has been show...
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04/08/2021
Pseudo-supervised Deep Subspace Clustering
Auto-Encoder (AE)-based deep subspace clustering (DSC) methods have achi...
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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...
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11/03/2020
Kernel Two-Dimensional Ridge Regression for Subspace Clustering
Subspace clustering methods have been widely studied recently. When the ...
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08/31/2020
Structured Graph Learning for Clustering and Semi-supervised Classification
Graphs have become increasingly popular in modeling structures and inter...
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07/11/2020
Relation-Guided Representation Learning
Deep auto-encoders (DAEs) have achieved great success in learning data r...
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05/19/2020
Two-Dimensional Semi-Nonnegative Matrix Factorization for Clustering
In this paper, we propose a new Semi-Nonnegative Matrix Factorization me...
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12/03/2019
Multi-view Subspace Clustering via Partition Fusion
Multi-view clustering is an important approach to analyze multi-view dat...
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12/03/2019
Structure Learning with Similarity Preserving
Leveraging on the underlying low-dimensional structure of data, low-rank...
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11/21/2019
Large-scale Multi-view Subspace Clustering in Linear Time
A plethora of multi-view subspace clustering (MVSC) methods have been pr...
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09/16/2019
Multi-graph Fusion for Multi-view Spectral Clustering
A panoply of multi-view clustering algorithms has been developed to deal...
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09/13/2019
Multiple Partitions Aligned Clustering
Multi-view clustering is an important yet challenging task due to the di...
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09/09/2019
Latent Multi-view Semi-Supervised Classification
To explore underlying complementary information from multiple views, in ...
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07/09/2019
Nonnegative Matrix Factorization with Local Similarity Learning
Existing nonnegative matrix factorization methods focus on learning glob...
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05/21/2019
Clustering with Similarity Preserving
Graph-based clustering has shown promising performance in many tasks. A ...
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04/16/2019
RES-PCA: A Scalable Approach to Recovering Low-rank Matrices
Robust principal component analysis (RPCA) has drawn significant attenti...
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03/14/2019
Low-rank Kernel Learning for Graph-based Clustering
Constructing the adjacency graph is fundamental to graph-based clusterin...
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03/11/2019
Similarity Learning via Kernel Preserving Embedding
Data similarity is a key concept in many data-driven applications. Many ...
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12/17/2018
Robust Graph Learning from Noisy Data
Learning graphs from data automatically has shown encouraging performanc...
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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...
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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...
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11/12/2017
Unified Spectral Clustering with Optimal Graph
Spectral clustering has found extensive use in many areas. Most traditio...
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05/01/2017
Twin Learning for Similarity and Clustering: A Unified Kernel Approach
Many similarity-based clustering methods work in two separate steps incl...
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09/27/2016
A Fast Factorization-based Approach to Robust PCA
Robust principal component analysis (RPCA) has been widely used for reco...
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09/27/2016
Top-N Recommendation on Graphs
Recommender systems play an increasingly important role in online applic...
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02/25/2016
Top-N Recommendation with Novel Rank Approximation
The importance of accurate recommender systems has been widely recognize...
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01/19/2016
Top-N Recommender System via Matrix Completion
Top-N recommender systems have been investigated widely both in industry...
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11/17/2015
Robust PCA via Nonconvex Rank Approximation
Numerous applications in data mining and machine learning require recove...
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10/30/2015
Robust Subspace Clustering via Tighter Rank Approximation
Matrix rank minimization problem is in general NP-hard. The nuclear norm...
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08/18/2015
Robust Subspace Clustering via Smoothed Rank Approximation
Matrix rank minimizing subject to affine constraints arises in many appl...
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07/03/2015
