Artificial neural networks and machine learning - ICANN 2024 Part 9
.- 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..- R...
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| Sprache: | eng |
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2024
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| Schriftenreihe: | Lecture notes in computer science
15024 |
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| Online Zugang: | Cover |
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| Zusammenfassung: | .- 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 ConversationalRecommender 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 amongBuilding Fire Hazard..- DDPM-MoCo: Enhancing the Generation and Detection of Industrial Surface Defects throughGenerative 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 |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | xxxiv, 495 Seiten Diagramme |
| ISBN: | 9783031723551 978-3-031-72355-1 |