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Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part I
| Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part I |
| Autore | Senn Walter |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (1178 pages) |
| Disciplina | 006.32 |
| Altri autori (Persone) |
SanguinetiMarcello
SaudargieneAusra TetkoIgor V VillaAlessandro E. P JirsaViktor BengioYoshua |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-032-04558-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911047704203321 |
Senn Walter
|
||
| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part III
| Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part III |
| Autore | Senn Walter |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (639 pages) |
| Disciplina | 006.32 |
| Altri autori (Persone) |
SanguinetiMarcello
SaudargieneAusra TetkoIgor V VillaAlessandro E. P JirsaViktor BengioYoshua |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-032-04549-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911047684303321 |
|
Senn Walter
|
||
| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part III
| Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part III |
| Autore | Senn Walter |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (639 pages) |
| Disciplina | 006.32 |
| Altri autori (Persone) |
SanguinetiMarcello
SaudargieneAusra TetkoIgor V VillaAlessandro E. P JirsaViktor BengioYoshua |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-032-04549-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996678677403316 |
|
Senn Walter
|
||
| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part I
| Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part I |
| Autore | Senn Walter |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (1178 pages) |
| Disciplina | 006.32 |
| Altri autori (Persone) |
SanguinetiMarcello
SaudargieneAusra TetkoIgor V VillaAlessandro E. P JirsaViktor BengioYoshua |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-032-04558-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996678675003316 |
|
Senn Walter
|
||
| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part II
| Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part II |
| Autore | Senn Walter |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (1159 pages) |
| Disciplina | 006.32 |
| Altri autori (Persone) |
SanguinetiMarcello
SaudargieneAusra TetkoIgor V VillaAlessandro E. P JirsaViktor BengioYoshua |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-032-04546-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996678672503316 |
|
Senn Walter
|
||
| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part IV
| Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part IV |
| Autore | Senn Walter |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (787 pages) |
| Disciplina | 006.32 |
| Altri autori (Persone) |
SanguinetiMarcello
SaudargieneAusra TetkoIgor V VillaAlessandro E. P JirsaViktor BengioYoshua |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-032-04555-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996678669803316 |
|
Senn Walter
|
||
| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part II
| Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part II |
| Autore | Senn Walter |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (1159 pages) |
| Disciplina | 006.32 |
| Altri autori (Persone) |
SanguinetiMarcello
SaudargieneAusra TetkoIgor V VillaAlessandro E. P JirsaViktor BengioYoshua |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-032-04546-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911047714203321 |
|
Senn Walter
|
||
| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part IV
| Artificial Neural Networks and Machine Learning - ICANN 2025 : 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part IV |
| Autore | Senn Walter |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (787 pages) |
| Disciplina | 006.32 |
| Altri autori (Persone) |
SanguinetiMarcello
SaudargieneAusra TetkoIgor V VillaAlessandro E. P JirsaViktor BengioYoshua |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-032-04555-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911046540803321 |
|
Senn Walter
|
||
| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning [[electronic resource] ] : 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II / / edited by Igor V. Tetko, Věra Kůrková, Pavel Karpov, Fabian Theis
| Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning [[electronic resource] ] : 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II / / edited by Igor V. Tetko, Věra Kůrková, Pavel Karpov, Fabian Theis |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXX, 807 p. 294 illus., 193 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Artificial intelligence
Computer vision Computer engineering Computer networks Algorithms Data protection Artificial Intelligence Computer Vision Computer Engineering and Networks Computer Communication Networks Data and Information Security |
| ISBN | 3-030-30484-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Adaptive Graph Fusion for Unsupervised Feature Selection -- Unsupervised Feature Selection via Local Total-order Preservation -- Discrete Stochastic Search and its Application to Feature-Selection for Deep Relational Machines -- Joint Dictionary Learning for Unsupervised Feature Selection -- Comparison between Filter Criteria for Feature Selection in Regression -- CancelOut: A layer for feature selection in deep neural networks -- Adaptive-L2 Batch Neural Gas -- Application of Self Organizing Map to Preprocessing Input Vectors for Convolutional Neural Network -- Hierarchical Reinforcement Learning with Unlimited Recursive Subroutine Calls -- Automatic Augmentation by Hill Climbing -- Learning Camera-invariant Representation for Person Re-identification -- PA-RetinaNet: Path Augmented RetinaNet for Dense Object Detection -- Singular Value Decomposition and Neural Networks -- PCI: Principal Component Initialization for Deep Autoencoders -- Improving Weight Initialization of ReLU and Output Layers -- Post-synaptic potential regularization has potential -- A Novel Modification on the Levenberg-Marquardt Algorithm for Avoiding Overfitting in Neural Network Training -- Sign Based Derivative Filtering for Stochastic Gradient Descent -- Architecture-aware Bayesian Optimization for Neural Network Tuning -- Non-Convergence and Limit Cycles in the Adam Optimizer -- Learning Internal Dense But External Sparse Structures of Deep Convolutional Neural Network -- Using feature entropy to guide filter pruning for efficient convolutional networks -- Simultaneously Learning Architectures and Features of Deep Neural Networks -- Learning Sparse Hidden States in Long Short-Term Memory -- Multi-objective Pruning for CNNs using Genetic Algorithm -- Dynamically Sacrificing Accuracy for Reduced Computation: Cascaded Inference Based on Softmax Confidence -- Light-Weight Edge Enhanced Network for On-orbit Semantic Segmentation -- Local Normalization Based BN Layer Pruning -- On Practical Approach to Uniform Quantization of Non-redundant Neural Networks -- Residual learning for FC kernels of convolutional network -- A Novel Neural Network-based Symbolic Regression Method: Neuro-Encoded Expression Programming -- Compute-efficient neural network architecture optimization by a genetic algorithm -- Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures -- Predictive Uncertainty Estimation with Temporal Convolutional Networks for Dynamic Evolutionary Optimization -- Sparse Recurrent Mixture Density Networks for Forecasting High Variability Time Series with Confidence Estimates -- A multitask learning neural network for short-term traffic speed prediction and confidence estimation -- Central-diffused Instance Generation Method in Class Incremental Learning -- Marginal Replay vs Conditional Replay for Continual Learning -- Simplified computation and interpretation of Fisher matrices in incremental learning with deep neural networks -- Active Learning for Image Recognition using a Visualization-Based User Interface -- Basic Evaluation Scenarios for Incrementally Trained Classifiers -- Embedding Complexity of Learned Representations in Neural Networks -- Joint Metric Learning on Riemannian Manifold of Global Gaussian Distributions -- Multi-Task Sparse Regression Metric Learning for Heterogeneous Classification -- Fast Approximate Geodesics for Deep Generative Models -- Spatial Attention Network for Few-Shot Learning -- Routine Modeling with Time Series Metric Learning -- Leveraging Domain Knowledge for Reinforcement Learning using MMC Architectures -- Conditions for Unnecessary Logical Constraints in Kernel Machines -- HiSeqGAN: Hierarchical Sequence Synthesis and Prediction -- DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting -- Transferable Adversarial Cycle Alignment for Domain Adaption -- Evaluation of domain adaptation approaches for robust classification of heterogeneous biological data sets -- Named Entity Recognition for Chinese Social Media with Domain Adversarial Training and Language Modeling -- Deep Domain Knowledge Distillation for Person Re-identification -- A study on catastrophic forgetting in deep LSTM networks -- A Label-specific Attention-based Network with Regularized Loss for Multi-label Classification -- An Empirical Study of Multi-domain and Multi-task Learning in Chinese Named Entity Recognition -- Filter Method Ensemble with Neural Networks -- Dynamic Centroid Insertion and Adjustment for Data Sets with Multiple Imbalanced Classes -- Increasing the Generalisaton Capacity of Conditional VAEs -- Playing the Large Margin Preference Game. |
| Record Nr. | UNISA-996466303903316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning : 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II / / edited by Igor V. Tetko, Věra Kůrková, Pavel Karpov, Fabian Theis
| Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning : 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II / / edited by Igor V. Tetko, Věra Kůrková, Pavel Karpov, Fabian Theis |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXX, 807 p. 294 illus., 193 illus. in color.) |
| Disciplina |
006.3
006.32 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Artificial intelligence
Computer vision Computer engineering Computer networks Algorithms Data protection Artificial Intelligence Computer Vision Computer Engineering and Networks Computer Communication Networks Data and Information Security |
| ISBN | 3-030-30484-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Adaptive Graph Fusion for Unsupervised Feature Selection -- Unsupervised Feature Selection via Local Total-order Preservation -- Discrete Stochastic Search and its Application to Feature-Selection for Deep Relational Machines -- Joint Dictionary Learning for Unsupervised Feature Selection -- Comparison between Filter Criteria for Feature Selection in Regression -- CancelOut: A layer for feature selection in deep neural networks -- Adaptive-L2 Batch Neural Gas -- Application of Self Organizing Map to Preprocessing Input Vectors for Convolutional Neural Network -- Hierarchical Reinforcement Learning with Unlimited Recursive Subroutine Calls -- Automatic Augmentation by Hill Climbing -- Learning Camera-invariant Representation for Person Re-identification -- PA-RetinaNet: Path Augmented RetinaNet for Dense Object Detection -- Singular Value Decomposition and Neural Networks -- PCI: Principal Component Initialization for Deep Autoencoders -- Improving Weight Initialization of ReLU and Output Layers -- Post-synaptic potential regularization has potential -- A Novel Modification on the Levenberg-Marquardt Algorithm for Avoiding Overfitting in Neural Network Training -- Sign Based Derivative Filtering for Stochastic Gradient Descent -- Architecture-aware Bayesian Optimization for Neural Network Tuning -- Non-Convergence and Limit Cycles in the Adam Optimizer -- Learning Internal Dense But External Sparse Structures of Deep Convolutional Neural Network -- Using feature entropy to guide filter pruning for efficient convolutional networks -- Simultaneously Learning Architectures and Features of Deep Neural Networks -- Learning Sparse Hidden States in Long Short-Term Memory -- Multi-objective Pruning for CNNs using Genetic Algorithm -- Dynamically Sacrificing Accuracy for Reduced Computation: Cascaded Inference Based on Softmax Confidence -- Light-Weight Edge Enhanced Network for On-orbit Semantic Segmentation -- Local Normalization Based BN Layer Pruning -- On Practical Approach to Uniform Quantization of Non-redundant Neural Networks -- Residual learning for FC kernels of convolutional network -- A Novel Neural Network-based Symbolic Regression Method: Neuro-Encoded Expression Programming -- Compute-efficient neural network architecture optimization by a genetic algorithm -- Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures -- Predictive Uncertainty Estimation with Temporal Convolutional Networks for Dynamic Evolutionary Optimization -- Sparse Recurrent Mixture Density Networks for Forecasting High Variability Time Series with Confidence Estimates -- A multitask learning neural network for short-term traffic speed prediction and confidence estimation -- Central-diffused Instance Generation Method in Class Incremental Learning -- Marginal Replay vs Conditional Replay for Continual Learning -- Simplified computation and interpretation of Fisher matrices in incremental learning with deep neural networks -- Active Learning for Image Recognition using a Visualization-Based User Interface -- Basic Evaluation Scenarios for Incrementally Trained Classifiers -- Embedding Complexity of Learned Representations in Neural Networks -- Joint Metric Learning on Riemannian Manifold of Global Gaussian Distributions -- Multi-Task Sparse Regression Metric Learning for Heterogeneous Classification -- Fast Approximate Geodesics for Deep Generative Models -- Spatial Attention Network for Few-Shot Learning -- Routine Modeling with Time Series Metric Learning -- Leveraging Domain Knowledge for Reinforcement Learning using MMC Architectures -- Conditions for Unnecessary Logical Constraints in Kernel Machines -- HiSeqGAN: Hierarchical Sequence Synthesis and Prediction -- DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting -- Transferable Adversarial Cycle Alignment for Domain Adaption -- Evaluation of domain adaptation approaches for robust classification of heterogeneous biological data sets -- Named Entity Recognition for Chinese Social Media with Domain Adversarial Training and Language Modeling -- Deep Domain Knowledge Distillation for Person Re-identification -- A study on catastrophic forgetting in deep LSTM networks -- A Label-specific Attention-based Network with Regularized Loss for Multi-label Classification -- An Empirical Study of Multi-domain and Multi-task Learning in Chinese Named Entity Recognition -- Filter Method Ensemble with Neural Networks -- Dynamic Centroid Insertion and Adjustment for Data Sets with Multiple Imbalanced Classes -- Increasing the Generalisaton Capacity of Conditional VAEs -- Playing the Large Margin Preference Game. |
| Record Nr. | UNINA-9910349283803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
