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Toward fair graph neural networks via real counterfactual samples
Graph neural networks (GNNs) have become pivotal in various critical decision-making scenarios due to their exceptional performance. However,...
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Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
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DQMMBSC: design of an augmented deep Q-learning model for mining optimisation in IIoT via hybrid-bioinspired blockchain shards and contextual consensus
Single-chained blockchains are highly secure but cannot be scaled to larger IIoT (Internet of Industrial Things) network scenarios due to storage...
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HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer...
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Hierarchical adaptive evolution framework for privacy-preserving data publishing
The growing need for data publication and the escalating concerns regarding data privacy have led to a surge in interest in Privacy-Preserving Data...
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L2XGNN: learning to explain graph neural networks
Graph Neural Networks (GNNs) are a popular class of machine learning models. Inspired by the learning to explain (L2X) paradigm, we propose L2xGnn , a...
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Anomaly analytics in data-driven machine learning applications
Machine learning is used widely to create a range of prediction or classification models. The quality of the machine learning (ML) models depends not...
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Temporal analysis of computational economics: a topic modeling approach
This study offers a comprehensive investigation into the thematic evolution within computational economics over the past two decades, leveraging...
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Explainable dating of greek papyri images
Greek literary papyri, which are unique witnesses of antique literature, do not usually bear a date. They are thus currently dated based on...
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Compressed sensing: a discrete optimization approach
We study the Compressed Sensing (CS) problem, which is the problem of finding the most sparse vector that satisfies a set of linear measurements up...
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Assessing the cooling impact of the urban park during pre- and post-cyclone using Landsat images
Cities are far warmer than their surroundings. Using vegetation is one of the best techniques to mitigate the effects of urban heat islands (UHI)....
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Examining ALS: reformed PCA and random forest for effective detection of ALS
ALS (Amyotrophic Lateral Sclerosis) is a fatal neurodegenerative disease of the human motor system. It is a group of progressive diseases that...
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TOPCOAT: towards practical two-party Crystals-Dilithium
The development of threshold protocols based on lattice-signature schemes has been of increasing interest in the past several years. The main...
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MIM: A multiple integration model for intrusion detection on imbalanced samples
The quantity of normal samples is commonly significantly greater than that of malicious samples, resulting in an imbalance in network security data....
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FlexpushdownDB: rethinking computation pushdown for cloud OLAP DBMSs
Modern cloud-native OLAP databases adopt a storage-disaggregation architecture that separates the management of computation and storage. A major...
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Data reduction in big data: a survey of methods, challenges and future directions
Data reduction plays a pivotal role in managing and analyzing big data, which is characterized by its volume, velocity, variety, veracity, value,...
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Moreau-Yoshida variational transport: a general framework for solving regularized distributional optimization problems
We address a general optimization problem involving the minimization of a composite objective functional defined over a class of probability...
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Multi-task learning and mutual information maximization with crossmodal transformer for multimodal sentiment analysis
The effectiveness of multimodal sentiment analysis hinges on the seamless integration of information from diverse modalities, where the quality of...
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Unveiling the impact of employee-customer familiarity on customer purchase intentions: an empirical investigation within the realm of web-based date analytics
This research delves into the intricate dynamics of employee-customer familiarity and its profound influence on customer purchase intentions within...
