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Poster: A Comparative Analysis of Machine Learning Models for SAT Runtime Prediction

Year: 2025

Type: conference-paper

Source: IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)

DOI: 10.1109/rtcsa66114.2025.00035

Authors: Tomohisa Kawakami, Tomoyasu Shimada, Xiangbo Kong, Hiroyuki Tomiyama, Shigeru Yamashita

Institutions: Duke University, Ritsumeikan University, Toyama Prefectural University

Language: English

Topic: Constraint Satisfaction and Optimization

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W7084095444

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Cites: 4

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