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245 1 0 _aArtificial Neural Networks and Machine Learning - ICANN 2024
_h[electronic resource] :
_b33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17-20, 2024, Proceedings, Part I /
_cedited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXXXIII, 480 p. 149 illus., 128 illus. in color.
_bonline resource.
336 _atext
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337 _acomputer
_bc
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338 _aonline resource
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347 _atext file
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490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v15016
505 0 _a -- Theory of Neural Networks and Machine Learning. -- Multi-label Robust Feature Selection via Subspace-Sparsity Learning. -- Nullspace-based metric for classification of dynamical systems and sensors. -- On the Bayesian Interpretation of Robust Regression Neural Networks. -- Probability-Generating Function Kernels for Spherical Data. -- Tailored Finite Point Operator Networks for Interface problems. -- Novel Methods in Machine Learning. -- A Simple Task-aware Contrastive Local Descriptor Selection Strategy for Few-shot Learning between inter class and intra class. -- Adaptive Compression of the Latent Space in Variational Autoencoders. -- Asymmetric Isomap for Dimensionality Reduction and Data Visualization. -- CALICO: Confident Active Learning with Integrated Calibration. -- Improved Multi-hop Reasoning through Sampling and Aggregating. -- Learning Solutions of Stochastic Optimization Problems with Bayesian Neural Networks. -- Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations. -- Safe Data Resampling Method based on Counterfactuals Analysis. -- Test-Time Augmentation for Traveling Salesperson Problem. -- Novel Neural Architectures. -- Resonator-Gated RNNs. -- Towards a model of associative memory with learned distributed representations. -- Neural Architecture Search. -- Accelerated NAS via pretrained ensembles and multi-fidelity Bayesian Optimization. -- Feature Activation-Driven Zero-Shot NAS: A Contrastive Learning Framework. -- NAS-Bench-Compre: A Comprehensive Neural Architecture Search Benchmark with Customizable Components. -- NAVIGATOR-D3: Neural Architecture search using VarIational Graph Auto-encoder Toward Optimal aRchitecture Design for Diverse Datasets. -- ResBuilder: Automated Learning of Depth with Residual Structures -- Self-Organization. -- A Neuron Coverage-based Self-Organizing Approach for RBFNNs in Multi-Class Classification Tasks. -- Self-Organising Neural Discrete Representation Learning à la Kohonen. -- Neural Processes. -- Combined Global and Local Information Diffusion of Neural Processes. -- Topology of Neural Processes. -- Novel Architectures for Computer Vision. -- DEEPAM: Toward Deeper Attention Module in Residual Convolutional Neural Networks. -- Differentiable Largest Connected Component Layer for Image Mattin. -- Enhancing Generalization in Convolutional Neural Networks through Regularization with Edge and Line Features. -- Transformer Tracker based on Multi-level Residual Perception Structure. .-Multimodal Architectures. -- CAW: Confidence-based Adaptive Weighted Model for Multi-modal Entity Linking. -- Exploring Interpretable Semantic Alignment for Multimodal Machine Translation. -- Fairness in Machine Learning. -- CFP: A Reinforcement Learning Framework for Comprehensive Fairness-Performance Trade-off in Machine Learning.
520 _aThe 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.
541 _fUABC ;
_cPerpetuidad
650 0 _aArtificial intelligence.
650 0 _aComputers.
650 0 _aApplication software.
650 0 _aComputer networks .
650 1 4 _aArtificial Intelligence.
650 2 4 _aComputing Milieux.
650 2 4 _aComputer and Information Systems Applications.
650 2 4 _aComputer Communication Networks.
700 1 _aWand, Michael.
_eeditor.
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700 1 _aMalinovská, Kristína.
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700 1 _aSchmidhuber, Jürgen.
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700 1 _aTetko, Igor V.
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710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9783031723339
830 0 _aLecture Notes in Computer Science,
_x1611-3349 ;
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856 4 0 _zLibro electrónico
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