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Artificial Neural Networks and Machine Learning - ICANN 2024 = 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17-20, 2024 : proceedings.. Part IX /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Artificial Neural Networks and Machine Learning - ICANN 2024/ edited by Michael Wand ... [et al.].
其他題名:	33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17-20, 2024 : proceedings.
其他題名:	ICANN 2024
其他作者:	Wand, Michael.
團體作者:	International Conference on Artificial Neural Networks (European Neural Network Society)
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	xxxiv, 495 p. :ill. (some col.), digital ;24 cm.
內容註:	Human-Computer Interfaces. -- Combining Contrastive Learning and Sequence Learning for Automated Essay Scoring. -- PIDM: Personality-aware Interaction Diffusion Model for gesture generation. -- Prompt Design using Past Dialogue Summarization for LLMs to Generate the Current Appropriate Dialogue. -- Recommender Systems. -- Click-Through Rate Prediction Based on Filtering-enhanced with Multi-Head Attention. -- Enhancing Sequential Recommendation via Aligning Interest Distributions. -- LGCRS: LLM-Guided Representation-Enhancing for Conversational Recommender System. -- Multi-intent Aware Contrastive Learning for Sequential Recommendation. -- Subgraph Collaborative Graph Contrastive Learning for Recommendation. -- Time-Aware Squeeze-Excitation Transformer for Sequential Recommendation. -- Environment and Climate. -- Carbon Price Forecasting with LLM-based Refinement and Transfer-Learning. -- Challenges, Methods, Data - a Survey of Machine Learning in Water Distribution Networks. -- Day-ahead scenario analysis of wind power based on ICGAN and IDTW-Kmedoids. -- Enhancing Weather Predictions: Super-Resolution via Deep Diffusion Models. -- Hybrid CNN-MLP for Wastewater Quality Estimation. -- Short-term Forecasting of Wind Power Using CEEMDAN-ICOA-GRU Model. -- City Planning. -- Predicting City Origin-Destination Flow with Generative Pre-training. -- Vehicle-based Evolutionary Travel Time Estimation with Deep Meta Learning. -- Machine Learning in Engineering and Industry. -- APF-DQN: Adaptive Objective Pathfinding via Improved Deep Reinforcement Learning among Building Fire Hazard. -- DDPM-MoCo: Enhancing the Generation and Detection of Industrial Surface Defects through Generative and Contrastive Learning. -- Detecting Railway Track Irregularities Using Conformal Prediction. -- Identifying the Trends of Technological Convergence between Domains using a Heterogeneous Graph Perspective: A Case Study of the Graphene Industry. -- Machine Learning Accelerated Prediction of 3D Granular Flows in Hoppers. -- RD-Crack: A Study of Concrete Crack Detection Guided by a Residual Neural Network Improved Based on Diffusion Modeling. -- Applications in Finance. -- Anomaly Detection in Blockchain Using Multi-source Embedding and Attention Mechanism. -- Beyond Gut Feel: Using Time Series Transformers to Find Investment Gems. -- MSIF: Multi-Source Information Fusion for Financial Question Answering. -- Artificial Intelligence in Education. -- A Temporal-Enhanced Model for Knowledge Tracing. -- Social Network Analysis. -- Position and type aware anchor link prediction across social networks. -- Artificial Intelligence and Music. -- LSTM-MorA: Melody-Accompaniment Classification of MIDI Tracks. -- Software Security. -- Ch4os: Discretized Generative Adversarial Network for Functionality-preserving Evasive Modification on Malware. -- SSA-GAT: Graph-based Self-supervised Learning for Network Intrusion Detection.
Contained By:	Springer Nature eBook
標題:	Neural networks (Computer science) - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-72356-8
ISBN:	9783031723568

Artificial Neural Networks and Machine Learning - ICANN 2024 = 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17-20, 2024 : proceedings.. Part IX /
Artificial Neural Networks and Machine Learning - ICANN 202433rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17-20, 2024 : proceedings.Part IX /[electronic resource] :ICANN 2024edited by Michael Wand ... [et al.]. - Cham :Springer Nature Switzerland :2024. - xxxiv, 495 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,150240302-9743 ;. - Lecture notes in computer science,15024..

Human-Computer Interfaces. -- Combining Contrastive Learning and Sequence Learning for Automated Essay Scoring. -- PIDM: Personality-aware Interaction Diffusion Model for gesture generation. -- Prompt Design using Past Dialogue Summarization for LLMs to Generate the Current Appropriate Dialogue. -- Recommender Systems. -- Click-Through Rate Prediction Based on Filtering-enhanced with Multi-Head Attention. -- Enhancing Sequential Recommendation via Aligning Interest Distributions. -- LGCRS: LLM-Guided Representation-Enhancing for Conversational Recommender System. -- Multi-intent Aware Contrastive Learning for Sequential Recommendation. -- Subgraph Collaborative Graph Contrastive Learning for Recommendation. -- Time-Aware Squeeze-Excitation Transformer for Sequential Recommendation. -- Environment and Climate. -- Carbon Price Forecasting with LLM-based Refinement and Transfer-Learning. -- Challenges, Methods, Data - a Survey of Machine Learning in Water Distribution Networks. -- Day-ahead scenario analysis of wind power based on ICGAN and IDTW-Kmedoids. -- Enhancing Weather Predictions: Super-Resolution via Deep Diffusion Models. -- Hybrid CNN-MLP for Wastewater Quality Estimation. -- Short-term Forecasting of Wind Power Using CEEMDAN-ICOA-GRU Model. -- City Planning. -- Predicting City Origin-Destination Flow with Generative Pre-training. -- Vehicle-based Evolutionary Travel Time Estimation with Deep Meta Learning. -- Machine Learning in Engineering and Industry. -- APF-DQN: Adaptive Objective Pathfinding via Improved Deep Reinforcement Learning among Building Fire Hazard. -- DDPM-MoCo: Enhancing the Generation and Detection of Industrial Surface Defects through Generative and Contrastive Learning. -- Detecting Railway Track Irregularities Using Conformal Prediction. -- Identifying the Trends of Technological Convergence between Domains using a Heterogeneous Graph Perspective: A Case Study of the Graphene Industry. -- Machine Learning Accelerated Prediction of 3D Granular Flows in Hoppers. -- RD-Crack: A Study of Concrete Crack Detection Guided by a Residual Neural Network Improved Based on Diffusion Modeling. -- Applications in Finance. -- Anomaly Detection in Blockchain Using Multi-source Embedding and Attention Mechanism. -- Beyond Gut Feel: Using Time Series Transformers to Find Investment Gems. -- MSIF: Multi-Source Information Fusion for Financial Question Answering. -- Artificial Intelligence in Education. -- A Temporal-Enhanced Model for Knowledge Tracing. -- Social Network Analysis. -- Position and type aware anchor link prediction across social networks. -- Artificial Intelligence and Music. -- LSTM-MorA: Melody-Accompaniment Classification of MIDI Tracks. -- Software Security. -- Ch4os: Discretized Generative Adversarial Network for Functionality-preserving Evasive Modification on Malware. -- SSA-GAT: Graph-based Self-supervised Learning for Network Intrusion Detection.

The ten-volume set LNCS 15016-15025 constitutes the refereed proceedings of the 33rd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2024, held in Lugano, Switzerland, during September 17-20, 2024. The 294 full papers and 16 short papers included in these proceedings were carefully reviewed and selected from 764 submissions. The papers cover the following topics: Part I - theory of neural networks and machine learning; novel methods in machine learning; novel neural architectures; neural architecture search; self-organization; neural processes; novel architectures for computer vision; and fairness in machine learning. Part II - computer vision: classification; computer vision: object detection; computer vision: security and adversarial attacks; computer vision: image enhancement; and computer vision: 3D methods. Part III - computer vision: anomaly detection; computer vision: segmentation; computer vision: pose estimation and tracking; computer vision: video processing; computer vision: generative methods; and topics in computer vision. Part IV - brain-inspired computing; cognitive and computational neuroscience; explainable artificial intelligence; robotics; and reinforcement learning. Part V - graph neural networks; and large language models. Part VI - multimodality; federated learning; and time series processing. Part VII - speech processing; natural language processing; and language modeling. Part VIII - biosignal processing in medicine and physiology; and medical image processing. Part IX - human-computer interfaces; recommender systems; environment and climate; city planning; machine learning in engineering and industry; applications in finance; artificial intelligence in education; social network analysis; artificial intelligence and music; and software security. Part X - workshop: AI in drug discovery; workshop: reservoir computing; special session: accuracy, stability, and robustness in deep neural networks; special session: neurorobotics; and special session: spiking neural networks.

ISBN: 9783031723568

Standard No.: 10.1007/978-3-031-72356-8doiSubjects--Topical Terms:

582186
Neural networks (Computer science)
--Congresses.

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

Artificial Neural Networks and Machine Learning - ICANN 2024 = 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17-20, 2024 : proceedings.. Part IX /
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