A Course Teacher Recommendation Method Based on an Improved Weighted Bipartite Graph and Slope One
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3228957
Abstract: The quality of course teaching is directly related to education quality. Many scholars have attempted to identify the associations between course-teaching quality and teachers’ characteristics, such as educational background, degree, professional title, age, teaching age,… read more here.
Keywords: weighted bipartite; quality; bipartite graph; course ... See more keywords
BGCFI: Efficient Verification in Fine-Grained Control-Flow Integrity Based on Bipartite Graph
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3234184
Abstract: Control-flow integrity (CFI) is considered a principled mitigation against control-flow hijacking even under the most powerful attacker who can arbitrarily write and read memory. However, existing schemes still demonstrated limitations in either guaranteeing high security… read more here.
Keywords: bipartite graph; fine grained; control flow;
Fuzzy Embedded Clustering Based on Bipartite Graph for Large-Scale Hyperspectral Image
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3073035
Abstract: Hyperspectral image (HSI) clustering has been widely used in the field of remote sensing. However, most traditional clustering algorithms are not suitable for dealing with large-scale HSI due to their low clustering performance and high… read more here.
Keywords: large scale; fuzzy clustering; hyperspectral image; based bipartite ... See more keywords
Graph Simplification-Aided ADMM for Decentralized Composite Optimization
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2019.2953538
Abstract: In this article, we consider the problem of decentralized composite optimization over a connected and symmetric graph, in which each node holds its own agent-specific private convex functions, and communications are only allowed between nodes… read more here.
Keywords: simplest bipartite; composite optimization; decentralized composite; graph ... See more keywords
Learning an Optimal Bipartite Graph for Subspace Clustering via Constrained Laplacian Rank.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2021.3113520
Abstract: In this article, we focus on utilizing the idea of co-clustering algorithms to address the subspace clustering problem. In recent years, co-clustering methods have been developed greatly with many important applications, such as document clustering… read more here.
Keywords: laplacian rank; bipartite graph; graph; subspace clustering ... See more keywords
A Bipartite Graph Partition-Based Coclustering Approach With Graph Nonnegative Matrix Factorization for Large Hyperspectral Images
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3097358
Abstract: Clustering large hyperspectral images (HSIs) is a very challenging problem because large HSIs have high dimensionality, large spectral variability, and large computational and memory consumption. Recently, sparse subspace clustering (SSC) has achieved remarkable success in… read more here.
Keywords: matrix; graph partition; graph; hsis ... See more keywords
Multiview Spectral Clustering With Bipartite Graph
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3171411
Abstract: Multi-view spectral clustering has become appealing due to its good performance in capturing the correlations among all views. However, on one hand, many existing methods usually require a quadratic or cubic complexity for graph construction… read more here.
Keywords: bipartite graph; graph; complementary information; spectral clustering ... See more keywords
Co-Clustering on Bipartite Graphs for Robust Model Fitting
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3214073
Abstract: Recently, graph-based methods have been widely applied to model fitting. However, in these methods, association information is invariably lost when data points and model hypotheses are mapped to the graph domain. In this paper, we… read more here.
Keywords: bipartite graph; bipartite graphs; clustering bipartite; model ... See more keywords
L-BGNN: Layerwise Trained Bipartite Graph Neural Networks.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3171199
Abstract: Learning low-dimensional representations of bipartite graphs enables e-commerce applications, such as recommendation, classification, and link prediction. A layerwise-trained bipartite graph neural network (L-BGNN) embedding method, which is unsupervised, efficient, and scalable, is proposed in this… read more here.
Keywords: bipartite graph; trained bipartite; graph neural; layerwise ... See more keywords
Fast Clustering by Directly Solving Bipartite Graph Clustering Problem.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3219131
Abstract: Spectral clustering (SC) has been widely used in many applications and shows excellent performance. Its high computational cost limits its applications; many strategies including the anchor technique can partly alleviate the high computational cost problem.… read more here.
Keywords: problem; directly solving; fast clustering; bipartite graph ... See more keywords
A Bipartite Graph Neural Network Approach for Scalable Beamforming Optimization
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Wireless Communications"
DOI: 10.1109/twc.2022.3193138
Abstract: Deep learning (DL) techniques have been intensively studied for the optimization of multi-user multiple-input single-output (MU-MISO) downlink systems owing to the capability of handling nonconvex formulations. However, the fixed computation structure of existing deep neural… read more here.
Keywords: neural network; bipartite graph; beamforming optimization; graph neural ... See more keywords