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Artificial Neural Networks and Machine Learning - ICANN 2025 - 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part III

Englisch · Taschenbuch

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The four-volume set LNCS 16068-16071 constitutes the proceedings of the 34th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2025, held in Kaunas, Lithuania, September 9 12, 2025.
The 170 full papers and 8 abstracts included in these conference proceedings were carefully reviewed and selected from 375 submissions. The conference strongly values the synergy between theoretical progress and impactful real-world applications, and actively encourages contributions that demonstrate how artificial neural networks are being used to address pressing societal and technological challenges.

Inhaltsverzeichnis

.- ACGCN: A Sequence-Attention-Based Graph Convolutional Model for Enhanced Recommendation Systems.
.- Hyperparameter-Free Bi-Level Knowledge Graph Optimization for Link Prediction.
.- SWIFT: State-space Wavelet Integrated Forecasting Technology for Enhanced Time Series Prediction.
.- Federated Privacy-Preserving for Cross-Domain Sequential Recommendation.
.- An Enhanced Audio Feature Tailored for Anomalous Sound Detection Based on Pre-trained Models.
.- Multimodal Sentiment Analysis with Parallel Attention and Correlation Fusion.
.- A Hybrid Learning Approach for Continual Knowledge Graph Embedding: Contrastive Masking and Joint Anti-Forgetting.
.- Leveraging Machine-Translated Data for Sentiment Analysis in Low-Resource Languages: A Case Study on Bengal.
.- RRetFC: Leveraging Recursive Retrieval For LLM-Enhanced Complex Fact-Checking.
.- Feature-Aware Sequence Models for Tabular Data Processing with Missing Values.
.- Topic-Driven Hyper-Relational Knowledge Graphs with Adaptive Reconstruction for Multi-Hop Question Answering Using LLMs.
.- Toward Better Document-Level Relation Extraction: De-Sampling and Mixture of Experts in Action.
.- ConSens: Assessing context grounding in open-book question answering.
.- ChiMDQA: Towards Comprehensive Chinese Document QA with Fine-grained Evaluation.
.- Emotional Text-to-Speech via Style Decoder with Emotion Shared Styleformer Block and RoPE Prior Encoder.
.- Can LLM-Generated Textual Explanations Enhance Model Classification Performance? An Empirical Study.
.- Early Acoustic and Vision Cross-modal Interation Learning for Multimal Sentiment Analysis.
.- Uncovering Causal Relation Shifts in Event Sequences under Out-of-Domain Interventions.
.- Sustainable techniques to improve Data Quality for training image-based explanatory models for Recommender Systems.
.- TimeFlowDiffuser: A Hierarchical Diffusion Framework with Adaptive Context Sampling for Multi-Horizon Time Series Forecasting.
.- ConDTab: Conditional Diffusion Transformer for Mixed-Type Tabular Synthesis with Dual Attention Latent Encoding.
.- SentiAug: Adaptive Keywords Replacement and Confidence-guided Self-training Selection for Robust Sentiment Classification.
.- Real-time and personalized product recommendations for large e-commerce platforms.
.- A Two-Stage Framework Integrating Prompt Learning and Fine-tuning for Code Summarization.
.- DialGACL: Nonlinear Graph Attention Reasoning with Contrastive Learning for Complex Dialogue Fact Verification.
.- TimbreAdv: Timbre Adversarial Attacks on Speaker Verification Systems.
.- Time Series Generation for Augmenting Multi-Channel Automotive Audio Data.
.- PGD: Probe Guided Decoding for Alignment.

Zusammenfassung

The four-volume set LNCS 16068-16071 constitutes the proceedings of the 34th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2025, held in Kaunas, Lithuania, September 9–12, 2025.
The 170 full papers and 8 abstracts included in these conference proceedings were carefully reviewed and selected from 375 submissions. The conference strongly values the synergy between theoretical progress and impactful real-world applications, and actively encourages contributions that demonstrate how artificial neural networks are being used to address pressing societal and technological challenges.

Produktdetails

Mitarbeit Yoshua Bengio (Herausgeber), Viktor Jirsa (Herausgeber), Marcello Sanguineti (Herausgeber), Ausra Saudargiene (Herausgeber), Ausra Saudargiene et al (Herausgeber), Walter Senn (Herausgeber), Igor V. Tetko (Herausgeber), Alessandro E. P. Villa (Herausgeber), Alessandro E.P Villa (Herausgeber)
Verlag Springer, Berlin
 
Sprache Englisch
Produktform Taschenbuch
Erschienen 06.10.2025
 
EAN 9783032045485
ISBN 978-3-0-3204548-5
Seiten 362
Abmessung 155 mm x 22 mm x 235 mm
Gewicht 604 g
Illustration XXXVII, 362 p. 91 illus., 86 illus. in color.
Serie Lecture Notes in Computer Science
Themen Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Informatik

machine learning, Robotics, Artificial Intelligence, Deep Learning, angewandte informatik, Informationstechnik (IT), allgemeine Themen, Netzwerk-Hardware, Classification, Neural Networks, Reinforcement Learning, Computer and Information Systems Applications, Computer Communication Networks, Image processing, Computing Milieux, Large Language Models, Reservoir Computing, Generative Models, Spiking Neural Networks, Graph Neural Networks

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