top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.

Biblioteca

MARC Lista (tabellare)
Advanced Mathematical Science for Mobility Society / / edited by Kazushi Ikeda, Yoshiumi Kawamura, Kazuhisa Makino, Satoshi Tsujimoto, Nobuo Yamashita, Shintaro Yoshizawa, Hanna Sumita
Advanced Mathematical Science for Mobility Society / / edited by Kazushi Ikeda, Yoshiumi Kawamura, Kazuhisa Makino, Satoshi Tsujimoto, Nobuo Yamashita, Shintaro Yoshizawa, Hanna Sumita
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (VIII, 215 p. 52 illus., 40 illus. in color.)
Disciplina 004.0151
Soggetto topico Computer science
Mathematical models
Quantitative research
Transportation engineering
Traffic engineering
Theory and Algorithms for Application Domains
Mathematical Modeling and Industrial Mathematics
Data Analysis and Big Data
Transportation Technology and Traffic Engineering
ISBN 981-9997-72-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part 1. Introduction, motivation, and direction for Advanced Mathematical Science for Mobility Society, together with the project between Toyota Motor Corporation and Kyoto University -- Chapter 1. Advanced Mathematical Science for Mobility Society -- Part 2. Mathematical models of flow Chapter. 2. Analysis of many-body particle systems by geometry and box-ball-system theory -- Chapter 3. Discrete Integrable Systems, LR transformations and Box-Ball Systems -- Part 3. Mathematical methods for huge data and network analysis -- Chapter 4. Eigenvalue Analysis in Mobility Data -- Chapter 5. Application of tensor network formalism for processing tensor data -- Chapter 6. Machine Learning Approach to Mobility Analysis -- Chapter 7. Graph optimization problems and algorithms for DAG-type blockchains -- Part 4. Algorithm for mobility society -- Chapter 8. Control and optimization of one-way car-sharing systems -- Chapter 9. Algorithms for future mobility society Chapter 10. Mechanism Design for Mobility.
Record Nr. UNINA-9910845080703321
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Neural Information Processing [[electronic resource] ] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part II / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Neural Information Processing [[electronic resource] ] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part II / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIX, 739 p. 252 illus.)
Disciplina 006.4
Collana Theoretical Computer Science and General Issues
Soggetto topico Pattern recognition systems
Computer vision
Artificial intelligence
Computer science
Data mining
Application software
Automated Pattern Recognition
Computer Vision
Artificial Intelligence
Theory of Computation
Data Mining and Knowledge Discovery
Computer and Information Systems Applications
ISBN 3-319-46672-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Deep and reinforcement learning -- Big data analysis -- Neural data analysis.-Robotics and control -- Bio-inspired/energy efficient information processing.-Whole brain architecture -- Neurodynamics -- Bioinformatics -- Biomedical engineering -- Data mining and cybersecurity workshop -- Machine learning.-Neuromorphic hardware -- Sensory perception -- Pattern recognition -- Social networks -- Brain-machine interface -- Computer vision -- Time series analysis.-Data-driven approach for extracting latent features -- Topological and graph based clustering methods -- Computational intelligence -- Data mining -- Deep neural networks -- Computational and cognitive neurosciences -- Theory and algorithms.
Record Nr. UNISA-996465374003316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Neural Information Processing [[electronic resource] ] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part IV / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Neural Information Processing [[electronic resource] ] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part IV / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIX, 663 p. 254 illus.)
Disciplina 006.32
Collana Theoretical Computer Science and General Issues
Soggetto topico Pattern recognition systems
Computer vision
Artificial intelligence
Computer science
Data mining
Application software
Automated Pattern Recognition
Computer Vision
Artificial Intelligence
Theory of Computation
Data Mining and Knowledge Discovery
Computer and Information Systems Applications
ISBN 3-319-46681-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Part IV -- Applications -- Classifying Human Activities with Temporal Extension of Random Forest -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Motivation and Justification -- 3 Temporal Extension of Random Forest -- 3.1 Preliminary -- 3.2 Temporal Sampling Mechanism -- 3.3 Temporal Randomization -- 4 Experimental Evaluation -- 4.1 Data Sets and Experimental Setup -- 4.2 Experimental Results -- 4.3 Performance Comparison -- 5 Conclusion -- References -- Echo State Network Ensemble for Human Motion Data Temporal Phasing: A Case Study on Tennis Forehands -- Abstract -- 1 Introduction -- 1.1 Related Work and Prior Studies -- 1.2 Temporal Phasing Analysis: Sport Science and Tennis Backgrounds -- 2 Experimental Setup: Data Collection and Visualisation of Temporal Phasing for Supervised Machine Learning -- 3 Data Analysis and Modelling -- 4 Classification Results and Discussion -- 5 Conclusions, Recommendations and Future Work -- Acknowledgements -- References -- Unregistered Bosniak Classification with Multi-phase Convolutional Neural Networks -- 1 Introduction -- 2 Bosniak Classification Problem -- 3 Algorithm -- 3.1 Data Acquisition -- 3.2 Data Augmentation -- 3.3 Multi-phase Convolutional Neural Network -- 4 Experiment -- 4.1 Single Convolutional Networks -- 4.2 Multi-phase Convolutional Networks -- 4.3 Implementation Details -- 5 Conclusion -- References -- Direct Estimation of Wrist Joint Angular Velocities from Surface EMGs by Using an SDNN Function Approximator -- 1 Introduction -- 2 Selective Desensitization Neural Network -- 3 Proposed Method -- 3.1 Surface EMG Acquisition -- 3.2 Signal Preprocessing -- 3.3 Function Approximation -- 4 Experiment -- 4.1 Method -- 4.2 Results -- 5 Conclusion -- References -- Data Analysis of Correlation Between Project Popularity and Code Change Frequency.
1 Introduction -- 2 Related Work -- 3 Research Method -- 4 Results and Analysis -- 5 Conclusion -- References -- Hidden Space Neighbourhood Component Analysis for Cancer Classification -- 1 Introduction -- 2 Hidden Space Neighbourhood Components Analysis -- 2.1 Algorithm Description -- 2.2 Hidden Function -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Setting and Results -- 4 Conclusions -- References -- Prediction of Bank Telemarketing with Co-training of Mixture-of-Experts and MLP -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Co-training -- 2.2 Mixture-of-Experts -- 2.3 Credit Scoring Using Machine Learning -- 3 Global-Local Co-training for Prediction -- 3.1 Global-Local Co-training Algorithm -- 3.2 Measuring Confidence Degree -- 4 Experiments -- 4.1 Bank Telemarketing Data -- 4.2 Experimental Results -- 5 Conclusion -- References -- Prioritising Security Tests on Large-Scale and Distributed Software Development Projects by Using Self-organised Maps -- 1 Introduction -- 2 Theoretical Background -- 2.1 Cyclomatic Complexity -- 2.2 Self-organising Maps -- 3 Contribution -- 4 Experiments -- 5 Conclusion -- References -- Android Malware Detection Method Based on Function Call Graphs -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Extraction of Structural Features of Android Apps -- 4 Malicious Code Detection Model -- 5 Experiments -- 5.1 Data Set Description -- 5.2 Experimental Results -- 6 Conclusion -- Acknowledgment -- References -- Proposal of Singular-Unit Restoration by Focusing on the Spatial Continuity of Topographical Statistics in Spectral Domain -- 1 Introduction -- 2 SU Restoration by Using Compex-Valued Neural Network -- 2.1 Principle of the Proposed Filter -- 2.2 Layered Complex-Valued Neural Network -- 3 Experimental Results -- 4 Conclusion -- References.
Inferring Users' Gender from Interests: A Tag Embedding Approach -- 1 Introduction -- 2 Related Work -- 2.1 Feature Set -- 2.2 Classification Method -- 3 A Conceptual Class Based Method -- 3.1 Building Initial Conceptual Classes -- 3.2 Expanding Conceptual Classes -- 3.3 Condensing Tag Space -- 4 Experimental Evaluation -- 4.1 Baselines -- 4.2 Effects of Parameters k and K -- 4.3 Effects of Three Expansion Strategies -- 4.4 Comparison with Baselines -- 5 Conclusion and Discussions -- References -- Fast Color Quantization via Fuzzy Clustering -- 1 Introduction -- 2 Employed Clustering Algorithms -- 3 Results and Discussion -- 4 Conclusions -- References -- Extended Dependency-Based Word Embeddings for Aspect Extraction -- 1 Introduction -- 2 Extending Dependency-Based Word Embeddings -- 2.1 Dependency-Based Word Embeddings -- 2.2 Extending Word Embeddings -- 2.3 Recurrent Neural Network Sequence Labeller -- 3 Experiment Settings -- 3.1 Data Set and Metric -- 3.2 Included Features -- 3.3 Word Embeddings -- 3.4 Training Parameters -- 3.5 Baselines -- 4 Results and Discussion -- 4.1 Comparison with Baselines -- 4.2 Comparison of Embeddings -- 4.3 Other Discussion -- 5 Conclusions -- References -- Topological Order Discovery via Deep Knowledge Tracing -- 1 Introduction -- 2 Related Work -- 3 Topological Order Discovery Model -- 3.1 Deep Knowledge Tracing Model -- 3.2 Topological Order Discovery -- 4 Experiments -- 4.1 Datasets -- 4.2 DKT Model Results -- 4.3 Topological Order Discovery Result -- 5 Future Work -- References -- PTR: Phrase-Based Topical Ranking for Automatic Keyphrase Extraction in Scientific Publications -- 1 Introduction -- 2 Methodology -- 2.1 Pre-processing -- 2.2 Topic Model Construction -- 2.3 Phrase-Based Topical Weighted-PageRank -- 2.4 Keyphrase Selection -- 3 Experiments -- 3.1 Datasets -- 3.2 Evaluation.
3.3 Influences of Parameters to PTR -- 3.4 Results of Comparing with Baseline Methods -- 4 Conclusion -- References -- Neural Network Based Association Rule Mining from Uncertain Data -- 1 Introduction -- 2 Association Rule Mining in Uncertain Data -- 3 Association Rule Mining on SOM Clusters -- 4 Experimentation and Analysis -- 5 Conclusion and Future Work -- References -- Analysis and Knowledge Discovery by Means of Self-Organizing Maps for Gaia Data Releases -- 1 Introduction -- 2 Self-Organizing Maps -- 3 Classification Tool -- 4 Features -- 5 Conclusion -- References -- Computational and Cognitive Neurosciences -- The Impact of Adaptive Regularization of the Demand Predictor on a Multistage Supply Chain Simulation -- 1 Introduction -- 2 Bullwhip Effect and Inventory Simulation -- 3 Appling Adaptive Regularization Models to Inventory Simulation -- 3.1 Demand Prediction Model in Inventory Simulation -- 3.2 Demand Prediction Using Adaptive Regularization of Weight Vectors -- 4 Experimental -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 4.3 Discussion -- 5 Conclusion -- References -- The Effect of Reward Information on Perceptual Decision-Making -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Participants -- 2.2 Stimuli -- 2.3 Experimental Design -- 2.4 Experimental Procedure -- 3 Analysis -- 4 Results -- 4.1 Post Reward Components -- 4.2 Post Stimulus Components -- 4.3 Early and Late Components -- 5 Discussion -- References -- Doubting What to Eat: A Computational Model for Food Choice Using Different Valuing Perspectives -- Abstract -- 1 Introduction -- 2 Background -- 3 The Computational Model -- 4 Simulation Results -- 5 Conclusion -- References -- A Novel Graph Regularized Sparse Linear Discriminant Analysis Model for EEG Emotion Recognition -- 1 Introduction -- 2 GraphSLDA Model -- 2.1 From LDA to LSR.
2.2 GraphSLDA -- 2.3 Optimization -- 2.4 Testing -- 3 Experiments -- 4 Conclusion -- References -- Information Maximization in a Feedforward Network Replicates the Stimulus Preference of the Medial Geniculate and the Auditory Cortex -- 1 Introduction -- 2 Model -- 3 Results -- 3.1 First-Output-Layer Neurons -- 3.2 Second-Output-Layer Neurons -- 4 Discussion -- References -- A Simple Visual Model Accounts for Drift Illusion and Reveals Illusory Patterns -- Abstract -- 1 Introduction -- 2 Reproduce Rotational Illusion Dependent on Background Luminance -- 2.1 Computational Model: Modified Lucas-Kanade Method [4] -- 2.2 Numerical Simulation: Rotational Directions and the Rotational Strength -- 2.3 Discussion -- 3 Model Predictions and Psychological Experiments -- 3.1 Circular Stimulus -- 3.2 Selection of Stimuli for Psychological Experiment -- 3.3 Methods -- 3.4 Correlation Between Model Estimation and Psychological Experiment -- 4 Conclusions -- Acknowledgements -- References -- An Internal Model of the Human Hand Affects Recognition of Graspable Tools -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- References -- Perceptual Representation of Material Quality: Adaptation to BRDF-Morphing Images -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Procedure -- 2.2 Stimuli -- 2.2.1 Selection of BRDF -- 2.2.2 Morphing BRDF -- 3 Expectation -- 4 Results -- 5 Conclusions and Discussion -- Acknowledgements -- References -- GPU-Accelerated Simulations of an Electric Stimulus and Neural Activities in Electrolocation -- 1 Introduction -- 2 Electrolocation -- 3 Methods -- 3.1 Models -- 3.2 Implementation -- 4 Results -- 5 Conclusion -- References -- Analysis of Similarity and Differences in Brain Activities Between Perception and Production of Facial Expressions Using EEG Data and the NeuCube Spiking Neural Network Architecture -- 1 Introduction.
2 The NeuCube Spiking Neural Network Architecture.
Record Nr. UNISA-996465570203316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Neural Information Processing [[electronic resource] ] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part III / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Neural Information Processing [[electronic resource] ] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part III / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XVIII, 651 p. 215 illus.)
Disciplina 006.3
Collana Theoretical Computer Science and General Issues
Soggetto topico Pattern recognition systems
Computer vision
Artificial intelligence
Computer science
Data mining
Application software
Automated Pattern Recognition
Computer Vision
Artificial Intelligence
Theory of Computation
Data Mining and Knowledge Discovery
Computer and Information Systems Applications
ISBN 3-319-46675-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part III -- Time Series Analysis -- Chaotic Feature Selection and Reconstruction in Time Series Prediction -- 1 Introduction -- 2 Chaotic Feature Selection and Reconstruction -- 2.1 Cooperative Neuro-Evolution -- 3 Experiments and Results -- 3.1 Problem Description -- 3.2 Experimental Design -- 3.3 Results and Discussion -- 4 Conclusions and Future Work -- References -- L1/2 Norm Regularized Echo State Network for Chaotic Time Series Prediction -- Abstract -- 1 Introduction -- 2 Echo State Networks -- 3 L1/2 Regularized Echo State Network -- 4 Simulations -- 5 Conclusions -- Acknowledgement -- References -- SVD and Text Mining Integrated Approach to Measure Effects of Disasters on Japanese Economics -- Abstract -- 1 Introduction -- 2 SVD and Text Mining Integrated Approach -- 3 Time Series Stock Data Analysis -- 4 Topic Extraction Results -- 5 Conclusion -- Acknowledgement -- References -- Deep Belief Network Using Reinforcement Learning and Its Applications to Time Series Forecasting -- Abstract -- 1 Introduction -- 2 DBN with BP Learning (The Conventional Method) -- 2.1 DBN with RBM and MLP -- 3 DBN with SGA (The Proposed Method) -- 3.1 The Structure of ANNs with SGA -- 4 Prediction Experiments and Results -- 4.1 CATS Benchmark Time Series Data -- 4.2 Optimization of Meta Parameters -- 4.3 Experiments Result -- 5 Conclusion -- Acknowledgment -- References -- Neuron-Network Level Problem Decomposition Method for Cooperative Coevolution of Recurrent Networks for Time Series Prediction -- 1 Introduction -- 2 Neuron-Network Level Problem Decomposition -- 3 Experimental Setup -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Data-Driven Approach for Extracting Latent Features from Multi-dimensional Data -- Yet Another Schatten Norm for Tensor Recovery -- 1 Introduction.
2 Theoretical Results -- 2.1 New Norm -- 2.2 Properties -- 2.3 Tensor Recovery -- 3 Experimental Results -- 4 Conclusion -- References -- Memory of Reading Literature in a Hippocampal Network Model Based on Theta Phase Coding -- 1 Introduction -- 2 Computer Simulation -- 3 Results -- 4 Discussion -- References -- Combining Deep Learning and Preference Learning for Object Tracking -- 1 Introduction -- 2 Deep and Preference Learning Tracker -- 2.1 Deep Learning -- 2.2 Preference Learning -- 2.3 Model Update -- 3 Experiments -- 4 Conclusions -- References -- A Cost-Sensitive Learning Strategy for Feature Extraction from Imbalanced Data -- 1 Introduction -- 2 A Motivating Example -- 3 Theoretical Analysis -- 3.1 Imbalance Cost Ratio -- 3.2 Cost-Sensitive Principal Component Analysis (CSPCA) -- 3.3 Cost-Sensitive Non-negative Matrix Factorization (CSNMF) -- 3.4 Revisiting the Motivating Example -- 4 Experiments and Analysis -- 4.1 Experimental Framework -- 4.2 Analysis and Results -- 5 Conclusions and Future Work -- References -- Nonnegative Tensor Train Decompositions for Multi-domain Feature Extraction and Clustering -- 1 Introduction -- 2 Nonnegative Tensor Decomposition Models -- 2.1 NTD Model -- 2.2 NTT Model -- 2.3 NTT-Tucker Model: A Hybrid of the NTD and NTT Models -- 3 NTT-HALS: Proposed Algorithm for NTT and NTT-Tucker -- 3.1 NTT-HALS for NTT -- 3.2 NTT-HALS for NTT-Tucker -- 4 Experiments -- 4.1 Multi-domain Feature Extraction from ERP Data -- 4.2 Feature Extraction and Clustering from ORL Database of Face Images -- 5 Discussion -- References -- Hyper-parameter Optimization of Sticky HDP-HMM Through an Enhanced Particle Swarm Optimization -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Method: Hyperparameter Optimization -- 4.1 Random Search -- 4.2 Particle Swarm Optimization -- 4.3 Ring-Based Particle Swarm Optimization.
5 Experiment -- 5.1 Dataset -- 5.2 Synthetic Data Results -- 5.3 Tum Kitchen Dataset Results -- 6 Conclusion -- References -- Approximate Inference Method for Dynamic Interactions in Larger Neural Populations -- 1 Introduction -- 2 Methods -- 2.1 The State-Space Model of Neural Interactions -- 2.2 Approximation Methods for a Large-Scale Analysis -- 3 Results -- 4 Conclusion -- References -- Features Learning and Transformation Based on Deep Autoencoders -- 1 Introduction -- 2 Unsupervised Transformation of the Feature Space -- 2.1 Matrix Decomposition and Normalization -- 2.2 Diffusion Maps -- 2.3 Deep Autoencoders -- 3 Topological Clustering -- 4 Experimental Results -- 5 Conclusion -- References -- t-Distributed Stochastic Neighbor Embedding with Inhomogeneous Degrees of Freedom -- 1 Introduction -- 2 Stochastic Neighbor Embedding -- 3 t-Distributed Stochastic Neighbor Embedding -- 4 Inhomogeneous t-SNE -- 4.1 Degrees of Freedom -- 4.2 Cost Function and Its Gradient -- 4.3 Optimization -- 5 Experiments -- 5.1 Experiment 1 -- 5.2 Experiment 2 -- 6 Summary and Discussion -- References -- Topological and Graph Based Clustering Methods -- Parcellating Whole Brain for Individuals by Simple Linear Iterative Clustering -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects -- 2.2 Simple Linear Iterative Clustering (SLIC) -- 2.3 Evaluation Metrics -- 3 Experimental Results -- 4 Conclusion and Future Directions -- Acknowledgements -- References -- Overlapping Community Structure Detection of Brain Functional Network Using Non-negative Matrix Factorization -- 1 Introduction -- 2 Methods and Material -- 2.1 Association Matrix Construction with NASR -- 2.2 Community Detection with SNMF -- 2.3 Data Preparation -- 2.4 Experiment -- 3 Results and Discussion -- 3.1 Simulated Data Set -- 3.2 Real Resting-State fMRI Data Set.
4 Conclusion and Limitation -- References -- Collaborative-Based Multi-scale Clustering in Very High Resolution Satellite Images -- 1 Introduction -- 2 Multi-scale Communication Between Different Algorithms -- 3 Experimental Results -- 3.1 Description of the Data -- 3.2 Results -- 4 Conclusion -- References -- Towards Ontology Reasoning for Topological Cluster Labeling -- 1 Introduction and Motivations -- 2 Related Work -- 3 Preliminaries About Ontology and Reasoning -- 4 Hybrid Approach: SOM Ontology Based Labeling -- 4.1 Topological Unsupervised Learning Step -- 4.2 Ontology Based Map Labeling -- 5 Experiments -- 5.1 Satellite Images Classification -- 6 Conclusion and Future Work -- References -- Overlapping Community Detection Using Core Label Propagation and Belonging Function -- 1 Introduction -- 2 Label Propagation Algorithm -- 2.1 Standard Label Propagation -- 2.2 Label Propagation with Dams and Core Detection -- 3 Proposed Methods for Detection of Overlapping Communities -- 3.1 Function 1: Membership Function Based on the Density -- 3.2 Function 2 Membership Function Based on the Local Clustering Coefficient -- 3.3 Proposed Community Detection Algorithms -- 4 Evaluation Measures of Community Detection Algorithm, Benchmarks, Experiments and Discussion -- 4.1 Experiments -- 4.2 Comparative Analysis -- 5 Perspectives and Conclusion -- References -- A New Clustering Algorithm for Dynamic Data -- 1 Introduction -- 2 Growing Neural Gas -- 3 A New Two-Level Clustering Algorithm for GNG -- 4 Experimental Results -- 5 Conclusions and Perspectives -- References -- Reinforcement Learning -- Decentralized Stabilization for Nonlinear Systems with Unknown Mismatched Interconnections -- 1 Introduction -- 2 Problem Statement -- 3 Decentralized Controller Design and Stability Analysis -- 3.1 Optimal Control -- 3.2 Neural Network Implementation.
3.3 Stability Analysis -- 4 Simulation Study -- 5 Conclusion -- References -- Optimal Constrained Neuro-Dynamic Programming Based Self-learning Battery Management in Microgrids -- 1 Introduction -- 2 Problem Formulation -- 3 Iterative ADP Algorithm for Battery Management System -- 3.1 Derivations of the Iterative ADP Algorithm -- 4 Simulation Analysis -- 5 Conclusion -- References -- Risk Sensitive Reinforcement Learning Scheme Is Suitable for Learning on a Budget -- 1 Introduction -- 2 Incremental Learning on a Budget -- 2.1 Kernel Regression Based Learning on a Budget -- 2.2 Kernel Replacement Algorithm -- 3 Risk Sensitive Reinforcement Learning -- 4 Experimental Results -- 4.1 Results -- 5 Conclusion -- References -- A Kernel-Based Sarsa() Algorithm with Clustering-Based Sample Sparsification -- 1 Introduction -- 2 RL and Kernel Method -- 3 Clustering-Based Selective Kernel Sarsa() -- 3.1 Clustering-Based Novelty Criterion -- 3.2 Framework of CSKS() -- 4 Experiment and Results -- 4.1 Settings of Acrobot -- 4.2 Results -- 5 Conclusion -- References -- Sparse Kernel-Based Least Squares Temporal Difference with Prioritized Sweeping -- 1 Introduction -- 2 Background -- 3 Sparse Kernel-Based Least Squares Temporal Difference with Prioritized Sweeping (PS-SKLSTD) -- 3.1 Sparse Kernel-Based Least Squares Temporal Difference -- 3.2 Kernel-Based Prioritized Sweeping -- 3.3 PS-SKLSTD Algorithm -- 4 Experimental Results -- 4.1 Puddle World -- 4.2 Cart-Pole -- 5 Conclusions -- References -- Computational Intelligence -- Vietnamese POS Tagging for Social Media Text -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Tagging Method -- 5 Experiments -- 5.1 Experimental Setting -- 5.2 Models to Compare -- 5.3 Results -- 6 Conclusion -- References -- Scaled Conjugate Gradient Learning for Quaternion-Valued Neural Networks -- 1 Introduction -- 2 The HR Calculus.
3 Conjugate Gradient Algorithms.
Record Nr. UNISA-996465569103316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Neural Information Processing [[electronic resource] ] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part I / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Neural Information Processing [[electronic resource] ] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part I / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIX, 639 p. 250 illus.)
Disciplina 006.32
Collana Theoretical Computer Science and General Issues
Soggetto topico Pattern recognition systems
Computer vision
Artificial intelligence
Computer science
Data mining
Automated Pattern Recognition
Computer Vision
Artificial Intelligence
Theory of Computation
Data Mining and Knowledge Discovery
ISBN 3-319-46687-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Deep and reinforcement learning -- Big data analysis -- Neural data analysis.-Robotics and control -- Bio-inspired/energy efficient information processing.-Whole brain architecture -- Neurodynamics -- Bioinformatics -- Biomedical engineering -- Data mining and cybersecurity workshop -- Machine learning -- Neuromorphic hardware -- Sensory perception -- Pattern recognition -- Social networks -- Brain-machine interface -- Computer vision -- Time series analysis.-Data-driven approach for extracting latent features -- Topological and graph based clustering methods -- Computational intelligence -- Data mining -- Deep neural networks -- Computational and cognitive neurosciences -- Theory and algorithms.
Record Nr. UNISA-996465401303316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part II / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part II / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIX, 739 p. 252 illus.)
Disciplina 006.4
Collana Theoretical Computer Science and General Issues
Soggetto topico Pattern recognition systems
Computer vision
Artificial intelligence
Computer science
Data mining
Application software
Automated Pattern Recognition
Computer Vision
Artificial Intelligence
Theory of Computation
Data Mining and Knowledge Discovery
Computer and Information Systems Applications
ISBN 3-319-46672-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Deep and reinforcement learning -- Big data analysis -- Neural data analysis.-Robotics and control -- Bio-inspired/energy efficient information processing.-Whole brain architecture -- Neurodynamics -- Bioinformatics -- Biomedical engineering -- Data mining and cybersecurity workshop -- Machine learning.-Neuromorphic hardware -- Sensory perception -- Pattern recognition -- Social networks -- Brain-machine interface -- Computer vision -- Time series analysis.-Data-driven approach for extracting latent features -- Topological and graph based clustering methods -- Computational intelligence -- Data mining -- Deep neural networks -- Computational and cognitive neurosciences -- Theory and algorithms.
Record Nr. UNINA-9910483725103321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part IV / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part IV / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIX, 663 p. 254 illus.)
Disciplina 006.32
Collana Theoretical Computer Science and General Issues
Soggetto topico Pattern recognition systems
Computer vision
Artificial intelligence
Computer science
Data mining
Application software
Automated Pattern Recognition
Computer Vision
Artificial Intelligence
Theory of Computation
Data Mining and Knowledge Discovery
Computer and Information Systems Applications
ISBN 3-319-46681-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Part IV -- Applications -- Classifying Human Activities with Temporal Extension of Random Forest -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Motivation and Justification -- 3 Temporal Extension of Random Forest -- 3.1 Preliminary -- 3.2 Temporal Sampling Mechanism -- 3.3 Temporal Randomization -- 4 Experimental Evaluation -- 4.1 Data Sets and Experimental Setup -- 4.2 Experimental Results -- 4.3 Performance Comparison -- 5 Conclusion -- References -- Echo State Network Ensemble for Human Motion Data Temporal Phasing: A Case Study on Tennis Forehands -- Abstract -- 1 Introduction -- 1.1 Related Work and Prior Studies -- 1.2 Temporal Phasing Analysis: Sport Science and Tennis Backgrounds -- 2 Experimental Setup: Data Collection and Visualisation of Temporal Phasing for Supervised Machine Learning -- 3 Data Analysis and Modelling -- 4 Classification Results and Discussion -- 5 Conclusions, Recommendations and Future Work -- Acknowledgements -- References -- Unregistered Bosniak Classification with Multi-phase Convolutional Neural Networks -- 1 Introduction -- 2 Bosniak Classification Problem -- 3 Algorithm -- 3.1 Data Acquisition -- 3.2 Data Augmentation -- 3.3 Multi-phase Convolutional Neural Network -- 4 Experiment -- 4.1 Single Convolutional Networks -- 4.2 Multi-phase Convolutional Networks -- 4.3 Implementation Details -- 5 Conclusion -- References -- Direct Estimation of Wrist Joint Angular Velocities from Surface EMGs by Using an SDNN Function Approximator -- 1 Introduction -- 2 Selective Desensitization Neural Network -- 3 Proposed Method -- 3.1 Surface EMG Acquisition -- 3.2 Signal Preprocessing -- 3.3 Function Approximation -- 4 Experiment -- 4.1 Method -- 4.2 Results -- 5 Conclusion -- References -- Data Analysis of Correlation Between Project Popularity and Code Change Frequency.
1 Introduction -- 2 Related Work -- 3 Research Method -- 4 Results and Analysis -- 5 Conclusion -- References -- Hidden Space Neighbourhood Component Analysis for Cancer Classification -- 1 Introduction -- 2 Hidden Space Neighbourhood Components Analysis -- 2.1 Algorithm Description -- 2.2 Hidden Function -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Setting and Results -- 4 Conclusions -- References -- Prediction of Bank Telemarketing with Co-training of Mixture-of-Experts and MLP -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Co-training -- 2.2 Mixture-of-Experts -- 2.3 Credit Scoring Using Machine Learning -- 3 Global-Local Co-training for Prediction -- 3.1 Global-Local Co-training Algorithm -- 3.2 Measuring Confidence Degree -- 4 Experiments -- 4.1 Bank Telemarketing Data -- 4.2 Experimental Results -- 5 Conclusion -- References -- Prioritising Security Tests on Large-Scale and Distributed Software Development Projects by Using Self-organised Maps -- 1 Introduction -- 2 Theoretical Background -- 2.1 Cyclomatic Complexity -- 2.2 Self-organising Maps -- 3 Contribution -- 4 Experiments -- 5 Conclusion -- References -- Android Malware Detection Method Based on Function Call Graphs -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Extraction of Structural Features of Android Apps -- 4 Malicious Code Detection Model -- 5 Experiments -- 5.1 Data Set Description -- 5.2 Experimental Results -- 6 Conclusion -- Acknowledgment -- References -- Proposal of Singular-Unit Restoration by Focusing on the Spatial Continuity of Topographical Statistics in Spectral Domain -- 1 Introduction -- 2 SU Restoration by Using Compex-Valued Neural Network -- 2.1 Principle of the Proposed Filter -- 2.2 Layered Complex-Valued Neural Network -- 3 Experimental Results -- 4 Conclusion -- References.
Inferring Users' Gender from Interests: A Tag Embedding Approach -- 1 Introduction -- 2 Related Work -- 2.1 Feature Set -- 2.2 Classification Method -- 3 A Conceptual Class Based Method -- 3.1 Building Initial Conceptual Classes -- 3.2 Expanding Conceptual Classes -- 3.3 Condensing Tag Space -- 4 Experimental Evaluation -- 4.1 Baselines -- 4.2 Effects of Parameters k and K -- 4.3 Effects of Three Expansion Strategies -- 4.4 Comparison with Baselines -- 5 Conclusion and Discussions -- References -- Fast Color Quantization via Fuzzy Clustering -- 1 Introduction -- 2 Employed Clustering Algorithms -- 3 Results and Discussion -- 4 Conclusions -- References -- Extended Dependency-Based Word Embeddings for Aspect Extraction -- 1 Introduction -- 2 Extending Dependency-Based Word Embeddings -- 2.1 Dependency-Based Word Embeddings -- 2.2 Extending Word Embeddings -- 2.3 Recurrent Neural Network Sequence Labeller -- 3 Experiment Settings -- 3.1 Data Set and Metric -- 3.2 Included Features -- 3.3 Word Embeddings -- 3.4 Training Parameters -- 3.5 Baselines -- 4 Results and Discussion -- 4.1 Comparison with Baselines -- 4.2 Comparison of Embeddings -- 4.3 Other Discussion -- 5 Conclusions -- References -- Topological Order Discovery via Deep Knowledge Tracing -- 1 Introduction -- 2 Related Work -- 3 Topological Order Discovery Model -- 3.1 Deep Knowledge Tracing Model -- 3.2 Topological Order Discovery -- 4 Experiments -- 4.1 Datasets -- 4.2 DKT Model Results -- 4.3 Topological Order Discovery Result -- 5 Future Work -- References -- PTR: Phrase-Based Topical Ranking for Automatic Keyphrase Extraction in Scientific Publications -- 1 Introduction -- 2 Methodology -- 2.1 Pre-processing -- 2.2 Topic Model Construction -- 2.3 Phrase-Based Topical Weighted-PageRank -- 2.4 Keyphrase Selection -- 3 Experiments -- 3.1 Datasets -- 3.2 Evaluation.
3.3 Influences of Parameters to PTR -- 3.4 Results of Comparing with Baseline Methods -- 4 Conclusion -- References -- Neural Network Based Association Rule Mining from Uncertain Data -- 1 Introduction -- 2 Association Rule Mining in Uncertain Data -- 3 Association Rule Mining on SOM Clusters -- 4 Experimentation and Analysis -- 5 Conclusion and Future Work -- References -- Analysis and Knowledge Discovery by Means of Self-Organizing Maps for Gaia Data Releases -- 1 Introduction -- 2 Self-Organizing Maps -- 3 Classification Tool -- 4 Features -- 5 Conclusion -- References -- Computational and Cognitive Neurosciences -- The Impact of Adaptive Regularization of the Demand Predictor on a Multistage Supply Chain Simulation -- 1 Introduction -- 2 Bullwhip Effect and Inventory Simulation -- 3 Appling Adaptive Regularization Models to Inventory Simulation -- 3.1 Demand Prediction Model in Inventory Simulation -- 3.2 Demand Prediction Using Adaptive Regularization of Weight Vectors -- 4 Experimental -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 4.3 Discussion -- 5 Conclusion -- References -- The Effect of Reward Information on Perceptual Decision-Making -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Participants -- 2.2 Stimuli -- 2.3 Experimental Design -- 2.4 Experimental Procedure -- 3 Analysis -- 4 Results -- 4.1 Post Reward Components -- 4.2 Post Stimulus Components -- 4.3 Early and Late Components -- 5 Discussion -- References -- Doubting What to Eat: A Computational Model for Food Choice Using Different Valuing Perspectives -- Abstract -- 1 Introduction -- 2 Background -- 3 The Computational Model -- 4 Simulation Results -- 5 Conclusion -- References -- A Novel Graph Regularized Sparse Linear Discriminant Analysis Model for EEG Emotion Recognition -- 1 Introduction -- 2 GraphSLDA Model -- 2.1 From LDA to LSR.
2.2 GraphSLDA -- 2.3 Optimization -- 2.4 Testing -- 3 Experiments -- 4 Conclusion -- References -- Information Maximization in a Feedforward Network Replicates the Stimulus Preference of the Medial Geniculate and the Auditory Cortex -- 1 Introduction -- 2 Model -- 3 Results -- 3.1 First-Output-Layer Neurons -- 3.2 Second-Output-Layer Neurons -- 4 Discussion -- References -- A Simple Visual Model Accounts for Drift Illusion and Reveals Illusory Patterns -- Abstract -- 1 Introduction -- 2 Reproduce Rotational Illusion Dependent on Background Luminance -- 2.1 Computational Model: Modified Lucas-Kanade Method [4] -- 2.2 Numerical Simulation: Rotational Directions and the Rotational Strength -- 2.3 Discussion -- 3 Model Predictions and Psychological Experiments -- 3.1 Circular Stimulus -- 3.2 Selection of Stimuli for Psychological Experiment -- 3.3 Methods -- 3.4 Correlation Between Model Estimation and Psychological Experiment -- 4 Conclusions -- Acknowledgements -- References -- An Internal Model of the Human Hand Affects Recognition of Graspable Tools -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- References -- Perceptual Representation of Material Quality: Adaptation to BRDF-Morphing Images -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Procedure -- 2.2 Stimuli -- 2.2.1 Selection of BRDF -- 2.2.2 Morphing BRDF -- 3 Expectation -- 4 Results -- 5 Conclusions and Discussion -- Acknowledgements -- References -- GPU-Accelerated Simulations of an Electric Stimulus and Neural Activities in Electrolocation -- 1 Introduction -- 2 Electrolocation -- 3 Methods -- 3.1 Models -- 3.2 Implementation -- 4 Results -- 5 Conclusion -- References -- Analysis of Similarity and Differences in Brain Activities Between Perception and Production of Facial Expressions Using EEG Data and the NeuCube Spiking Neural Network Architecture -- 1 Introduction.
2 The NeuCube Spiking Neural Network Architecture.
Record Nr. UNINA-9910483790903321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part I / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part I / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIX, 639 p. 250 illus.)
Disciplina 006.32
Collana Theoretical Computer Science and General Issues
Soggetto topico Pattern recognition systems
Computer vision
Artificial intelligence
Computer science
Data mining
Automated Pattern Recognition
Computer Vision
Artificial Intelligence
Theory of Computation
Data Mining and Knowledge Discovery
ISBN 3-319-46687-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Deep and reinforcement learning -- Big data analysis -- Neural data analysis.-Robotics and control -- Bio-inspired/energy efficient information processing.-Whole brain architecture -- Neurodynamics -- Bioinformatics -- Biomedical engineering -- Data mining and cybersecurity workshop -- Machine learning -- Neuromorphic hardware -- Sensory perception -- Pattern recognition -- Social networks -- Brain-machine interface -- Computer vision -- Time series analysis.-Data-driven approach for extracting latent features -- Topological and graph based clustering methods -- Computational intelligence -- Data mining -- Deep neural networks -- Computational and cognitive neurosciences -- Theory and algorithms.
Record Nr. UNINA-9910483782703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part III / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part III / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XVIII, 651 p. 215 illus.)
Disciplina 006.3
Collana Theoretical Computer Science and General Issues
Soggetto topico Pattern recognition systems
Computer vision
Artificial intelligence
Computer science
Data mining
Application software
Automated Pattern Recognition
Computer Vision
Artificial Intelligence
Theory of Computation
Data Mining and Knowledge Discovery
Computer and Information Systems Applications
ISBN 3-319-46675-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part III -- Time Series Analysis -- Chaotic Feature Selection and Reconstruction in Time Series Prediction -- 1 Introduction -- 2 Chaotic Feature Selection and Reconstruction -- 2.1 Cooperative Neuro-Evolution -- 3 Experiments and Results -- 3.1 Problem Description -- 3.2 Experimental Design -- 3.3 Results and Discussion -- 4 Conclusions and Future Work -- References -- L1/2 Norm Regularized Echo State Network for Chaotic Time Series Prediction -- Abstract -- 1 Introduction -- 2 Echo State Networks -- 3 L1/2 Regularized Echo State Network -- 4 Simulations -- 5 Conclusions -- Acknowledgement -- References -- SVD and Text Mining Integrated Approach to Measure Effects of Disasters on Japanese Economics -- Abstract -- 1 Introduction -- 2 SVD and Text Mining Integrated Approach -- 3 Time Series Stock Data Analysis -- 4 Topic Extraction Results -- 5 Conclusion -- Acknowledgement -- References -- Deep Belief Network Using Reinforcement Learning and Its Applications to Time Series Forecasting -- Abstract -- 1 Introduction -- 2 DBN with BP Learning (The Conventional Method) -- 2.1 DBN with RBM and MLP -- 3 DBN with SGA (The Proposed Method) -- 3.1 The Structure of ANNs with SGA -- 4 Prediction Experiments and Results -- 4.1 CATS Benchmark Time Series Data -- 4.2 Optimization of Meta Parameters -- 4.3 Experiments Result -- 5 Conclusion -- Acknowledgment -- References -- Neuron-Network Level Problem Decomposition Method for Cooperative Coevolution of Recurrent Networks for Time Series Prediction -- 1 Introduction -- 2 Neuron-Network Level Problem Decomposition -- 3 Experimental Setup -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Data-Driven Approach for Extracting Latent Features from Multi-dimensional Data -- Yet Another Schatten Norm for Tensor Recovery -- 1 Introduction.
2 Theoretical Results -- 2.1 New Norm -- 2.2 Properties -- 2.3 Tensor Recovery -- 3 Experimental Results -- 4 Conclusion -- References -- Memory of Reading Literature in a Hippocampal Network Model Based on Theta Phase Coding -- 1 Introduction -- 2 Computer Simulation -- 3 Results -- 4 Discussion -- References -- Combining Deep Learning and Preference Learning for Object Tracking -- 1 Introduction -- 2 Deep and Preference Learning Tracker -- 2.1 Deep Learning -- 2.2 Preference Learning -- 2.3 Model Update -- 3 Experiments -- 4 Conclusions -- References -- A Cost-Sensitive Learning Strategy for Feature Extraction from Imbalanced Data -- 1 Introduction -- 2 A Motivating Example -- 3 Theoretical Analysis -- 3.1 Imbalance Cost Ratio -- 3.2 Cost-Sensitive Principal Component Analysis (CSPCA) -- 3.3 Cost-Sensitive Non-negative Matrix Factorization (CSNMF) -- 3.4 Revisiting the Motivating Example -- 4 Experiments and Analysis -- 4.1 Experimental Framework -- 4.2 Analysis and Results -- 5 Conclusions and Future Work -- References -- Nonnegative Tensor Train Decompositions for Multi-domain Feature Extraction and Clustering -- 1 Introduction -- 2 Nonnegative Tensor Decomposition Models -- 2.1 NTD Model -- 2.2 NTT Model -- 2.3 NTT-Tucker Model: A Hybrid of the NTD and NTT Models -- 3 NTT-HALS: Proposed Algorithm for NTT and NTT-Tucker -- 3.1 NTT-HALS for NTT -- 3.2 NTT-HALS for NTT-Tucker -- 4 Experiments -- 4.1 Multi-domain Feature Extraction from ERP Data -- 4.2 Feature Extraction and Clustering from ORL Database of Face Images -- 5 Discussion -- References -- Hyper-parameter Optimization of Sticky HDP-HMM Through an Enhanced Particle Swarm Optimization -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Method: Hyperparameter Optimization -- 4.1 Random Search -- 4.2 Particle Swarm Optimization -- 4.3 Ring-Based Particle Swarm Optimization.
5 Experiment -- 5.1 Dataset -- 5.2 Synthetic Data Results -- 5.3 Tum Kitchen Dataset Results -- 6 Conclusion -- References -- Approximate Inference Method for Dynamic Interactions in Larger Neural Populations -- 1 Introduction -- 2 Methods -- 2.1 The State-Space Model of Neural Interactions -- 2.2 Approximation Methods for a Large-Scale Analysis -- 3 Results -- 4 Conclusion -- References -- Features Learning and Transformation Based on Deep Autoencoders -- 1 Introduction -- 2 Unsupervised Transformation of the Feature Space -- 2.1 Matrix Decomposition and Normalization -- 2.2 Diffusion Maps -- 2.3 Deep Autoencoders -- 3 Topological Clustering -- 4 Experimental Results -- 5 Conclusion -- References -- t-Distributed Stochastic Neighbor Embedding with Inhomogeneous Degrees of Freedom -- 1 Introduction -- 2 Stochastic Neighbor Embedding -- 3 t-Distributed Stochastic Neighbor Embedding -- 4 Inhomogeneous t-SNE -- 4.1 Degrees of Freedom -- 4.2 Cost Function and Its Gradient -- 4.3 Optimization -- 5 Experiments -- 5.1 Experiment 1 -- 5.2 Experiment 2 -- 6 Summary and Discussion -- References -- Topological and Graph Based Clustering Methods -- Parcellating Whole Brain for Individuals by Simple Linear Iterative Clustering -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects -- 2.2 Simple Linear Iterative Clustering (SLIC) -- 2.3 Evaluation Metrics -- 3 Experimental Results -- 4 Conclusion and Future Directions -- Acknowledgements -- References -- Overlapping Community Structure Detection of Brain Functional Network Using Non-negative Matrix Factorization -- 1 Introduction -- 2 Methods and Material -- 2.1 Association Matrix Construction with NASR -- 2.2 Community Detection with SNMF -- 2.3 Data Preparation -- 2.4 Experiment -- 3 Results and Discussion -- 3.1 Simulated Data Set -- 3.2 Real Resting-State fMRI Data Set.
4 Conclusion and Limitation -- References -- Collaborative-Based Multi-scale Clustering in Very High Resolution Satellite Images -- 1 Introduction -- 2 Multi-scale Communication Between Different Algorithms -- 3 Experimental Results -- 3.1 Description of the Data -- 3.2 Results -- 4 Conclusion -- References -- Towards Ontology Reasoning for Topological Cluster Labeling -- 1 Introduction and Motivations -- 2 Related Work -- 3 Preliminaries About Ontology and Reasoning -- 4 Hybrid Approach: SOM Ontology Based Labeling -- 4.1 Topological Unsupervised Learning Step -- 4.2 Ontology Based Map Labeling -- 5 Experiments -- 5.1 Satellite Images Classification -- 6 Conclusion and Future Work -- References -- Overlapping Community Detection Using Core Label Propagation and Belonging Function -- 1 Introduction -- 2 Label Propagation Algorithm -- 2.1 Standard Label Propagation -- 2.2 Label Propagation with Dams and Core Detection -- 3 Proposed Methods for Detection of Overlapping Communities -- 3.1 Function 1: Membership Function Based on the Density -- 3.2 Function 2 Membership Function Based on the Local Clustering Coefficient -- 3.3 Proposed Community Detection Algorithms -- 4 Evaluation Measures of Community Detection Algorithm, Benchmarks, Experiments and Discussion -- 4.1 Experiments -- 4.2 Comparative Analysis -- 5 Perspectives and Conclusion -- References -- A New Clustering Algorithm for Dynamic Data -- 1 Introduction -- 2 Growing Neural Gas -- 3 A New Two-Level Clustering Algorithm for GNG -- 4 Experimental Results -- 5 Conclusions and Perspectives -- References -- Reinforcement Learning -- Decentralized Stabilization for Nonlinear Systems with Unknown Mismatched Interconnections -- 1 Introduction -- 2 Problem Statement -- 3 Decentralized Controller Design and Stability Analysis -- 3.1 Optimal Control -- 3.2 Neural Network Implementation.
3.3 Stability Analysis -- 4 Simulation Study -- 5 Conclusion -- References -- Optimal Constrained Neuro-Dynamic Programming Based Self-learning Battery Management in Microgrids -- 1 Introduction -- 2 Problem Formulation -- 3 Iterative ADP Algorithm for Battery Management System -- 3.1 Derivations of the Iterative ADP Algorithm -- 4 Simulation Analysis -- 5 Conclusion -- References -- Risk Sensitive Reinforcement Learning Scheme Is Suitable for Learning on a Budget -- 1 Introduction -- 2 Incremental Learning on a Budget -- 2.1 Kernel Regression Based Learning on a Budget -- 2.2 Kernel Replacement Algorithm -- 3 Risk Sensitive Reinforcement Learning -- 4 Experimental Results -- 4.1 Results -- 5 Conclusion -- References -- A Kernel-Based Sarsa() Algorithm with Clustering-Based Sample Sparsification -- 1 Introduction -- 2 RL and Kernel Method -- 3 Clustering-Based Selective Kernel Sarsa() -- 3.1 Clustering-Based Novelty Criterion -- 3.2 Framework of CSKS() -- 4 Experiment and Results -- 4.1 Settings of Acrobot -- 4.2 Results -- 5 Conclusion -- References -- Sparse Kernel-Based Least Squares Temporal Difference with Prioritized Sweeping -- 1 Introduction -- 2 Background -- 3 Sparse Kernel-Based Least Squares Temporal Difference with Prioritized Sweeping (PS-SKLSTD) -- 3.1 Sparse Kernel-Based Least Squares Temporal Difference -- 3.2 Kernel-Based Prioritized Sweeping -- 3.3 PS-SKLSTD Algorithm -- 4 Experimental Results -- 4.1 Puddle World -- 4.2 Cart-Pole -- 5 Conclusions -- References -- Computational Intelligence -- Vietnamese POS Tagging for Social Media Text -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Tagging Method -- 5 Experiments -- 5.1 Experimental Setting -- 5.2 Models to Compare -- 5.3 Results -- 6 Conclusion -- References -- Scaled Conjugate Gradient Learning for Quaternion-Valued Neural Networks -- 1 Introduction -- 2 The HR Calculus.
3 Conjugate Gradient Algorithms.
Record Nr. UNINA-9910483725203321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui