Buch, Englisch, 365 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 581 g
9th International Conference, ICMLSC 2025, Tokyo, Japan, January 24-26, 2025, Revised Selected Papers, Part I
Buch, Englisch, 365 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 581 g
Reihe: Communications in Computer and Information Science
ISBN: 978-981-966399-6
Verlag: Springer Nature Singapore
This two part-volume CCIS constitutes the refereed proceedings of 9th International Conference, ICMLSC 2025, in Tokyo, Japan in January 24–26, 2025.
The 39 full papers and 13 short papers included in this book were carefully reviewed and selected from 121 submissions. They follow the topical sections as below:
Part I : Multimodal Data Analysis and Model Optimization; Basic Theories of Machine Learning and Emerging Application Technologies; and Intelligent Recommendation System Design and Privacy Security.
Part II : Deep Learning Models and High-performance Computing; Data-driven Complex System Modeling and Intelligent Optimization Algorithms; and Image Analysis and Processing Methods based on AI.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
.- Multimodal Data Analysis and Model Optimization.
.- Utilizing Demographic Data and Insurance Claims History to Develop Machine Learning for Assessing Cardiovascular Disease Risk.
.- Comprehensive Framework for Artificial Intelligence and Big Data Integration in Higher Education.
.- Data Envelopment Analysis on Response Surface Method for Efficient Parameterization of Evolutionary Algorithms in Industrial Applications.
.- Feature Niching based Differential Evolution for Feature Selection on High-Dimensional Data.
.- Evaluating the Performance of Open-Source LLMs in Local RAG Systems: A Practical Study on Low-Carbon Data Applications.
.- Data Selection for Close-Domain Data in Medical Continual Pretraining: A Case Study on Data Selection via Importance Resampling (DSIR).
.- Improving Domain-Specific Data Question Answering with Deep and Cross-Lingual Transfer Learning.
.- Leveraging Co-occurrence Graphs and NLP for Enhanced Job-Skill Matching.
.- Risk Estimation with Active Labeling.
.- Basic Theories of Machine Learning and Emerging Application Technologies.
.- Using Machine Learning Techniques to Discriminate Good and Poor Sleepers in Virtual Reality Environment.
.- San Jose Urban Forest - An Open-Source Tree Canopy Surveying and Assessment Tool.
.- Towards A Machine Learning-Based Approach To Predicting Stock Price Volatility and Its Associated Risk in Egypt.
.- Lift And Shift Of Model Code Using Machine Learning Microservices With Generative AI Mapping Layer In Enterprise SaaS Applications.
.- Machine Learning-Driven Extended Creativity for Reshaping Traditional Artistic Pieces.
.- Towards AI/ML-powered Hybrid Project Management Strategy for the Healthcare Sector.
.- Enhancing Textual Deception Detection: A Fused Handcrafted Feature Approach with Machine Learning Models.
.- Machine Learning Models for Validating the Self-Declaration Conformity Assessment: Risk Evaluation.
.- Enterprise Credit Rating Framework Based on RCGNN.
.- Intelligent Recommendation System Design and Privacy Security.
.- Emotionally Unbiased Reinforcement Learning for Equilibrium-Seeking in Conflict-Driven Multi-Agent Systems.
.- Diversified Conversational Recommendation System.
.- Rule Extraction with Reject Option.
.- Poisoning Attacks Against Security-Aware Federated Recommendation System.
.- Applying Artificial Intelligence in Taiwan’s fin-tech: Exploring Usage Intention of Robo-advisor Service.
.- Detecting Social Bots Using Neural Networks with Social, Word Embedding, and Temporal Features.
.- Exploring Information Presentation and Sentiment Experience in Generative AI-Controlled Interfaces: A Case Study on Electric Bicycle Interaction.
.- Advanced Generative AI: A Multi-Modal Approach through conversational Chatbot and Intelligent Question Answering for Enhanced customer experience and assistance in Air Travel Domain.
