Philippe Fournier‐Viger
6 أوراق في مجموعة PaperMetrix
أوراق هذا المؤلف
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Maintenance of Discovered High Average-Utility Itemsets in Dynamic Databases
2018 · Applied Sciences
High-utility itemset mining (HUIM) is an extension of traditional frequent itemset mining, which considers both quantities and unit profits of items in a database to reveal highly profitable itemsets regardless of their size. High average-utility …
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Utility Mining Across Multi-Dimensional Sequences
2019 · arXiv (Cornell University)
Knowledge extraction from database is the fundamental task in database and data mining community, which has been applied to a wide range of real-world applications and situations. Different from the support-based mining models, the utility-oriented …
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Discovering Spatial High Utility Itemsets in Spatiotemporal Databases
2019
In real-world databases, high utility itemset (HUI) is an important class of regularities. Most previous studies have focused on mining HUIs in transactional databases and did not consider the spatiotemporal characteristics of items. In this …
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A Novel Correlation Gaussian Process Regression-Based Extreme Learning Machine
2022 · Research Square
Abstract One obvious defect of Extreme Learning Machine (ELM) is that the prediction performance of ELM is sensitive to the random initialization of input-layer weights and hidden-layer biases. GPRELM integrating Gaussian Process Regression (GPR) into …
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Categorical data clustering: 25 years beyond K-modes
2024 · arXiv (Cornell University)
The clustering of categorical data is a common and important task in computer science, offering profound implications across a spectrum of applications. Unlike purely numerical data, categorical data often lack inherent ordering as in nominal …
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Balancing Invariant and Specific Knowledge for Domain Generalization with Online Knowledge Distillation
2025
Recent research has demonstrated the effectiveness of knowledge distillation in Domain Generalization. However, existing approaches often overlook domain-specific knowledge and rely on an offline distillation strategy, limiting the effectiveness of knowledge transfer. To address these …