Neural Information Processing 21st International Conference, ICONIP 2014, Kuching, Malaysia, November 3-6, 2014. Proceedings, Part I /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Loo, Chu Kiong (Επιμελητής έκδοσης), Yap, Keem Siah (Επιμελητής έκδοσης), Wong, Kok Wai (Επιμελητής έκδοσης), Teoh, Andrew (Επιμελητής έκδοσης), Huang, Kaizhu (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2014.
• Σειρά: Lecture Notes in Computer Science, 8834
• Θέματα: Computer science.; Computers.; Data mining.; Artificial intelligence.; Image processing.; Pattern recognition.; Computer Science.; Pattern Recognition.; Image Processing and Computer Vision.; Artificial Intelligence (incl. Robotics).; Computation by Abstract Devices.; Data Mining and Knowledge Discovery.

The three volume set LNCS 8834, LNCS 8835, and LNCS 8836 constitutes the proceedings of the 21st International Conference on Neural Information Processing, ICONIP 2014, held in Kuching, Malaysia, in November 2014. The 231 full papers presented were carefully reviewed and selected from 375 submission...

Πίνακας περιεχομένων:

• Cognitive Science.-Transfer Entropy and Information Flow Patterns in Functional Brain Networks during Cognitive Activity
• Human Implicit Intent Discrimination Using EEG and Eye Movement
• Towards Establishing Relationships Between Human Arousal level and Motion Mass
• Estimating Nonlinear Spatiotemporal Membrane Dynamics in Active Dendrites
• Inter Subject Correlation of Brain Activity during Visuo-Motor Sequence Learning
• An Agent Response System based on Mirror Neuron and Theory of Mind
• Dynamic of Nitric Oxide Diffusion in Volume Transmission: Model and Validation
• A Computational Model of the Relation Between Regulation of Negative Emotions and Mood
• Neural Networks and Learning Systems - Theory and Design
• Low-cost Representation for Restricted Boltzmann Machines
• Add-if-Silent Rule for Training Multi-layered Convolutional Network Neocognitron
• Posterior Distribution Learning (PDL): A Novel Supervised Learning Framework Including Unlabeled Samples Distribution into Decision
• Computational Model of Neocortical Learning Process: Prototype
• Active Learning with Maximum Density and Minimum Redundancy
• One-to-Many Association Ability of Chaotic Quaternionic Multidirectional Associative Memory
• An Entropy-guided Adaptive Co-construction Method of State and Action Spaces in Reinforcement Learning
• A Nodes Reduction Procedure for RBFNDDA through Histogram
• Toroidal approximate identity neural networks are universal approximators
• Self-Organizing Neural Grove
• Transfer learning using the Online FMM model
• A supervised methodology to measure the variables contribution to a clustering
• Coupling between spatial consistency of neural ring and local eld potential coherence: A computational study
• Fading channel prediction based on self-optimizing neural networks
• Invariant Multiparameter Sensitivity of Oscillator Network
• Spatial-Temporal Saliency Feature Extraction For Robust Mean-Shift Tracker
• BOOSTRON: Boosting Based Perceptron Learning
• G-Stream: Growing Neural Gas over Data Stream
• Combining Active Learning and Semi-Supervised Learning Using Local and Global Consistency
• Complex-Valued Neural Networks
• Recent Progress and Future Directions
• A Cascade System of Simple Dynamic Binary Neural Networks and Its Sparsification
• A Model of V4 Neurons Based on Sparse Coding
• A fast and memory-efficient hierarchical graph clustering algorithm
• Hopfield-Type Associative Memory with Sparse Modular Networks
• Concept Drift Detection based on Anomaly Analysis
• Online learning for faulty RBF networks with the concurrent fault
• The Performance of the Stochastic DNN-kWTA network
• Modularity maximization adjusted by neural networks
• A dynamic pruning strategy for incremental learning on a budget
• Neural Computing with Concurrent Synchrony
• A Line-partitioned Heteroassociative Memory for Storing Binary Fresnel Hologram
• A Unified Framework for Privacy Preserving Data Clustering
• Spiking Neural Network with Lateral Inhibition for Reward-based Associative Learning
• Fuzzy Signature Neural Networks for Classification: Optimising the Structure
• Self-Organizing Map-based Probabilistic Associative Memory
• Neural Networks and Learning Systems – Applications
• A Causal Model for Disease Pathway Discovery
• Enhanced Non-linear Features for On-line Handwriting Recognition Using Deep Learning
• Recognizing Human Actions by Using the Evolving Remote Supervised Method of Spiking Neural Networks
• A Neural Networks Committee for the Contextual Bandit Problem
• Multi-step Predictions of Landslide Displacements based on Echo State Network
• Discrete-Time Nonlinear Generalized Policy Iteration for Optimal Control Using Neural Networks
• ANFIS-Based Model for Improved Paraphrase Rating Prediction
• Contextual Bandit for Active Learning: Active Thompson Sampling
• Choosing the Best Auto-encoder-based Bagging Classifier: An Empirical Study
• Classification of fMRI Data in the NeuCube Evolving Spiking Neural Network Architecture
• A hybrid approach to pixel data mining
• A Novel SOH Prediction Framework for the Lithium-ion Battery using Echo State Network
• Significance of Non-edge Priors in Gene Regulatory Network Reconstruction
• Robust Lane Detection Based On Convolutional Neural Network and Random Sample Consensus
• Learning Local Receptive Fields in Deep Belief Networks for Visual Feature Detection
• Adaptive Wavelet Extreme Learning Machine (AW-ELM) for Index Finger Recognition Using Two-Channel Electromyography
• Text Categorization Using an Automatically Generated Labelled Dataset: An Evaluation Study
• Online Recommender System Based on Social Network Regularization
• A Nonlinear Cross-site Transfer Learning Approach for Recommender Systems
• Deep Learning of Multifractal Attributes from Motor Imagery Induced EEG
• A Fast Neural-Dynamical Approach to Scale-Invariant Object Detection
• Improving Quantization Quality in Brain-inspired Self-organization for Non-stationary Data Spaces
• Utilizing High-Dimensional Neural Networks for Pseudo-Orthogonalization of Memory Patterns
• Adaptive Noise Schedule for Denoising Autoencoder
• Modeling Bi-Directional Tree Contexts by Generative Transductions.-A Novel Architecture for Capturing Discrete Sequences Using Self-Organizing Maps.-An Improved Gbest Guided Artificial Bee Colony Algorithm for Classification and Prediction Tasks
• Artifact Removal from EEG using a Multi-Objective Independent Component Analysis Model.-Cooperative Feature Level Data Fusion For Authentication Using Neural Networks.-Fuzzy Output Error as the Performance Function for Training Artificial Neural Networks to Predict Reading Comprehension from Eye Gaze.-Part-based Tracking with Appearance Learning and Structural Constrains Estimation of Hidden Markov Chains by a Neural Network.-Corporate Leaders Analytics and Network System (CLANS): Constructing and Mining Social Networks among Corporations and Business Elites in China.-Characteristics and Potential Developments of Multiple-MLP Ensemble Re-RX Algorithm.