LEADER 00857nam a2200241 i 4500 001 991001875479707536 005 20020508183138.0 008 011023s1981 it ||| | ita 035 $ab1092582x-39ule_inst 035 $aPARLA150392$9ExL 040 $aDip.to Scienze Storiche Fil. e Geogr.$bita 100 1 $aMina, Giuseppe$06647 245 10$aAd ognuno la sua stella /$cP. Giuseppe Mina 260 $aBologna :$bEMI,$c1981 300 $a60 p: ;$c18,5 cm. 490 0 $aUomini e missione ;$v4 650 4$aGilardino, Ernesto - Missionario 907 $a.b1092582x$b23-02-17$c28-06-02 912 $a991001875479707536 945 $aLE009 STOR.44-56$g1$i2009000073852$lle009$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i11030069$z28-06-02 996 $aAd ognuno la sua stella$9920104 997 $aUNISALENTO 998 $ale009$b01-01-01$cm$da $e-$fita$git $h0$i1 LEADER 07055nam 22006375 450 001 9910698650003321 005 20260605212007.0 010 $a9783031301056$b(electronic bk.) 024 7 $a10.1007/978-3-031-30105-6 035 $a(MiAaPQ)EBC7236701 035 $a(Au-PeEL)EBL7236701 035 $a(OCoLC)1376446116 035 $a(DE-He213)978-3-031-30105-6 035 $a(PPN)269655174 035 $a(CKB)26435286900041 035 $a(EXLCZ)9926435286900041 100 $a20230412d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNeural Information Processing $e29th International Conference, ICONIP 2022, Virtual Event, November 22?26, 2022, Proceedings, Part I /$fedited by Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (660 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v13623 311 08$aPrint version: Tanveer, Mohammad Neural Information Processing Cham : Springer International Publishing AG,c2023 9783031301049 320 $aIncludes bibliographical references and index. 327 $aTheory and Algorithms -- Solving Partial Differential Equations using Point-based Neural Networks -- Patch Mix Augmentation with Dual Encoders for Meta-Learning -- Tacit Commitments Emergence in Multi-agent Reinforcement Learning -- Saccade Direction Information Channel -- Shared-Attribute Multi-Graph Clustering with Global Self-Attention -- Mutual Diverse-Label Adversarial Training -- Multi-Agent Hyper-Attention Policy Optimization -- Filter Pruning via Similarity Clustering for Deep Convolutional Neural Networks -- FPD: Feature Pyramid Knowledge Distillation -- An effective ensemble model related to incremental learning in neural machine translation -- Local-Global Semantic Fusion Single-shot Classification Method -- Self-Reinforcing Feedback Domain Adaptation Channel -- General Algorithm for Learning from Grouped Uncoupled Data and Pairwise Comparison Data -- Additional Learning for Joint Probability Distribution Matching in BiGAN -- Multi-View Self-Attention for Regression Domain Adaptation with Feature Selection -- EigenGRF: Layer-Wise Eigen-Learning for Controllable Generative Radiance Fields -- Partial Label learning with Gradually Induced Error-Correction Output Codes -- HMC-PSO: A Hamiltonian Monte Carlo and Particle Swarm Optimization-based optimizer -- Heterogeneous Graph Representation for Knowledge Tracing -- Intuitionistic fuzzy universum support vector machine -- Support vector machine based models with sparse auto-encoder based features for classification problem -- Selectively increasing the diversity of GAN-generated samples -- Cooperation and Competition: Flocking with Evolutionary Multi-Agent Reinforcement Learning -- Differentiable Causal Discovery Under Heteroscedastic Noise -- IDPL: Intra-subdomain adaptation adversarial learning segmentation method based on Dynamic Pseudo Labels -- Adaptive Scaling for U-Net in Time Series Classification -- Permutation Elementary Cellular Automata: Analysis and Application of Simple Examples -- SSPR: A Skyline-Based Semantic Place Retrieval Method -- Double Regularization-based RVFL and edRVFL Networks for Sparse-Dataset Classification -- Adaptive Tabu Dropout for Regularization of Deep Neural Networks -- Class-Incremental Learning with Multiscale Distillation for Weakly Supervised Temporal Action Localization -- Nearest Neighbor Classifier with Margin Penalty for Active Learning -- Factual Error Correction in Summarization with Retriever-Reader Pipeline -- Context-adapted Multi-policy Ensemble Method for Generalization in Reinforcement Learning -- Self-attention based multi-scale graph convolutional networks -- Synesthesia Transformer with Contrastive Multimodal Learning -- Context-based Point Generation Network for Point Cloud Completion -- Temporal Neighborhood Change Centrality for Important Node Identification in Temporal Networks -- DOM2R-Graph: A Web Attribute Extraction Architecture with Relation-aware Heterogeneous Graph Transformer -- Sparse Linear Capsules for Matrix Factorization-based Collaborative Filtering -- PromptFusion: a Low-cost Prompt-based Task Composition for Multi-task Learning -- A fast and efficient algorithm for filtering the training dataset -- Entropy-minimization Mean Teacher for Source-Free Domain Adaptive Object Detection -- IA-CL: A Deep Bidirectional Competitive Learning Method for Traveling Salesman Problem -- Boosting Graph Convolutional Networks With Semi-Supervised Training -- Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs -- VAAC: V-value Attention Actor-Critic for Cooperative Multi-agent Reinforcement Learning -- An Analytical Estimation of Spiking Neural Networks Energy Efficiency -- Correlation Based Semantic Transfer with Application to Domain Adaptation -- Minimum Variance Embedded Intuitionistic Fuzzy Weighted Random Vector Functional Link Network -- Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction. 330 $aThe three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22?26, 2022. The 146 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v13623 606 $aPattern recognition systems 606 $aData mining 606 $aMachine learning 606 $aSocial sciences$xData processing 606 $aAutomated Pattern Recognition 606 $aData Mining and Knowledge Discovery 606 $aMachine Learning 606 $aComputer Application in Social and Behavioral Sciences 615 0$aPattern recognition systems. 615 0$aData mining. 615 0$aMachine learning. 615 0$aSocial sciences$xData processing. 615 14$aAutomated Pattern Recognition. 615 24$aData Mining and Knowledge Discovery. 615 24$aMachine Learning. 615 24$aComputer Application in Social and Behavioral Sciences. 676 $a006.3 702 $aTanveer$b Mohammad 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910698650003321 996 $aNeural Information Processing$92554499 997 $aUNINA