001481095 000__ 06973cam\\2200625\i\4500 001481095 001__ 1481095 001481095 003__ OCoLC 001481095 005__ 20231031003322.0 001481095 006__ m\\\\\o\\d\\\\\\\\ 001481095 007__ cr\cn\nnnunnun 001481095 008__ 230926s2023\\\\sz\a\\\\o\\\\\101\0\eng\d 001481095 019__ $$a1399379189 001481095 020__ $$a9783031442131$$q(electronic bk.) 001481095 020__ $$a303144213X$$q(electronic bk.) 001481095 020__ $$z9783031442124 001481095 0247_ $$a10.1007/978-3-031-44213-1$$2doi 001481095 035__ $$aSP(OCoLC)1399536245 001481095 040__ $$aGW5XE$$beng$$epn$$erda$$cGW5XE$$dOCLKB$$dOCLKB$$dEBLCP$$dOCLKB 001481095 049__ $$aISEA 001481095 050_4 $$aQA76.87 001481095 08204 $$a006.3/2$$223/eng/20230926 001481095 1112_ $$aInternational Conference on Artificial Neural Networks (European Neural Network Society)$$n(32nd :$$d2023 :$$cĒrakleion, Greece) 001481095 24510 $$aArtificial neural networks and machine learning - ICANN 2023 :$$b32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26-29, 2023 : proceedings.$$nPart III /$$cLazaros Iliadis, Antonios Papaleonidas, Plamen Angelov, Chrisina Jayne, editors. 001481095 24630 $$aICANN 2023 001481095 264_1 $$aCham :$$bSpringer,$$c[2023] 001481095 264_4 $$c©2023 001481095 300__ $$a1 online resource (xxxv, 593 pages) :$$billustrations (chiefly color). 001481095 336__ $$atext$$btxt$$2rdacontent 001481095 337__ $$acomputer$$bc$$2rdamedia 001481095 338__ $$aonline resource$$bcr$$2rdacarrier 001481095 4901_ $$aLecture notes in computer science ;$$v14256 001481095 500__ $$aInternational conference proceedings. 001481095 500__ $$aIncludes author index. 001481095 5050_ $$aAnomaly Detection in Directed Dynamic Graphs via RDGCN and LSTAN -- Anomaly-Based Insider Threat Detection via Hierarchical Information Fusion -- CSEDesc: CyberSecurity Event Detection with Event Description -- GanNeXt: A New Convolutional GAN for Anomaly Detection -- K-Fold Cross-Valuation for Machine Learning Using Shapley Value -- Malicious Domain Detection Based on Self-supervised HGNNs with Contrastive Learning -- Time Series Anomaly Detection with Reconstruction-Based State-Space Models -- ReDualSVG: Refined Scalable Vector Graphics Generation -- Rethinking Feature Context in Learning Image-guided Depth Completion -- Semantic and Frequency Representation Mining for Face Manipulation Detection -- Single image dehazing network based on serial feature attention -- SS-Net: 3D Spatial-Spectral Network for Cerebrovascular Segmentation in TOF-MRA -- STAN: Spatio-Temporal Alignment Network for No-Reference Video Quality Assessment -- Style Expansion without Forgetting for Handwritten Character Recognition -- TransVQ-VAE: Generating Diverse Images using Hierarchical Representation Learning -- UG-Net: Unsupervised-Guided Network for Biomedical Image Segmentation and Classification -- Unsupervised Shape Enhancement and Factorization Machine Network for 3D Face Reconstruction -- Visible-Infrared Person Re-Identification via Modality Augmentation and Center Constraints -- Water Conservancy Remote Sensing Image Classification Based on Target-Scene Deep Semantic Enhancement -- A Partitioned Detection Architecture for Oriented Objects -- A Personalized Federated Multi-Task Learning Scheme for Encrypted Traffic Classification -- Addressing delays in Reinforcement Learning via Delayed Adversarial Imitation Learning -- An Evaluation of Self-Supervised Learning for Portfolio Diversification -- An exploitation-enhanced Bayesian optimization algorithm for high-dimensional expensive problems -- Balancing Selection and Diversity in Ensemble Learning with Exponential Mixture Model -- CIPER: Combining Invariant and Equivariant Representations Using Contrastive and Predictive Learning -- Contrastive Learning and the Emergence of Attributes Associations -- Contrastive Learning for Sleep Staging based on Inter Subject Correlation -- Diffusion Policies as Multi-Agent Reinforcement Learning Strategies -- Dynamic Memory-based Continual Learning with Generating and Screening -- Enhancing Text2SQL Generation with Syntactic Infor-mation and Multi-Task Learning -- Fast Generalizable Novel View Synthesis with Uncertainty-Aware Sampling -- Find Important Training Dataset by Observing the Training Sequence Similarity -- Generating Question-Answer Pairs for Few-shot Learning -- GFedKRL: Graph Federated Knowledge Re-Learning for Effective Molecular Property Prediction via Privacy Protection -- Gradient-Boosted Based Structured and Unstructured Learning -- Graph Federated Learning Based on the Decentralized Framework -- Heterogeneous Federated Learning Based on Graph Hypernetwork -- Learning to Resolve Conflicts in Multi-Task Learning -- Neighborhood-oriented Decentralized Learning Communication in Multi-Agent System -- NN-Denoising: A Low-Noise Distantly Supervised Document-Level Relation Extraction Scheme using Natural Language Inference and Negative Sampling -- pFedLHNs: Personalized Federated Learning via Local Hypernetworks -- Prototype Contrastive Learning for Personalized Federated Learning -- PTSTEP: Prompt Tuning for Semantic Typing of Event Processes -- SR-IDS: A Novel Network Intrusion Detection System Based on Self-taught Learning and Representation Learning -- Task-Aware Adversarial Feature Perturbation for Cross-Domain Few-Shot Learning -- Ternary Data, Triangle Decoding, Three Tasks, a Multitask Learning Speech Translation Model. 001481095 506__ $$aAccess limited to authorized users. 001481095 520__ $$aThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 2629, 2023. The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications. . 001481095 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 26, 2023). 001481095 650_0 $$aNeural networks (Computer science)$$vCongresses.$$vCongresses$$0(DLC)sh2008108385 001481095 650_0 $$aMachine learning$$vCongresses.$$vCongresses$$0(DLC)sh2008107143 001481095 650_0 $$aArtificial intelligence$$vCongresses.$$xMedical applications$$0(DLC)sh 88003000 001481095 655_0 $$aElectronic books. 001481095 655_7 $$aConference papers and proceedings.$$2lcgft 001481095 7001_ $$aIliadis, Lazaros S.,$$eeditor.$$0(OCoLC)oca08617580 001481095 7001_ $$aPapaleonidas, Antonios,$$eeditor. 001481095 7001_ $$aAngelov, Plamen P.,$$eeditor. 001481095 7001_ $$aJayne, Chrisina,$$eeditor.$$0(Uk)008383335 001481095 830_0 $$aLecture notes in computer science ;$$v14256. 001481095 852__ $$bebk 001481095 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-44213-1$$zOnline Access$$91397441.1 001481095 909CO $$ooai:library.usi.edu:1481095$$pGLOBAL_SET 001481095 980__ $$aBIB 001481095 980__ $$aEBOOK 001481095 982__ $$aEbook 001481095 983__ $$aOnline 001481095 994__ $$a92$$bISE