Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation

Table of Contents

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   Book Overview
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   Chapter 1 Bidirectional Associative Memory with Block Coding: A Comparison of Iterative Retrieval Methods
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   Chapter 2 Stability Analysis of a Generalized Class of BAM Neural Networks with Mixed Delays
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   Chapter 3 Dissipativity Analysis of a Class of Competitive Neural Networks with Proportional Delays
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   Chapter 4 A Nonlinear Fokker-Planck Description of Continuous Neural Network Dynamics
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   Chapter 5 Multi-modal Associative Storage and Retrieval Using Hopfield Auto-associative Memory Network
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   Chapter 6 Chaotic Complex-Valued Associative Memory with Adaptive Scaling Factor Independent of Multi-values
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   Chapter 7 A Comparative Analysis of Preprocessing Methods for Single-Trial Event Related Potential Detection
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   Chapter 8 Sleep State Analysis Using Calcium Imaging Data by Non-negative Matrix Factorization
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    Chapter 9 Detection of Directional Information Flow Induced by TMS Based on Symbolic Transfer Entropy
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    Chapter 10 Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network
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    Chapter 11 Distinguishing Violinists and Pianists Based on Their Brain Signals
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    Chapter 12 Research on Image-to-Image Translation with Capsule Network
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    Chapter 13 Multi-View Capsule Network
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    Chapter 15 DDRM-CapsNet: Capsule Network Based on Deep Dynamic Routing Mechanism for Complex Data
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    Chapter 16 Squeezed Very Deep Convolutional Neural Networks for Text Classification
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    Chapter 17 NeuroPower: Designing Energy Efficient Convolutional Neural Network Architecture for Embedded Systems
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    Chapter 18 Swap Kernel Regression
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    Chapter 19 Model-Agnostic Explanations for Decisions Using Minimal Patterns
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    Chapter 20 NARPCA: Neural Accumulate-Retract PCA for Low-Latency High-Throughput Processing on Datastreams
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    Chapter 21 An Evaluation of Various Regression Models for the Prediction of Two-Terminal Network Reliability
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    Chapter 22 Capsule Generative Models
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    Chapter 23 Evaluating CNNs on the Gestalt Principle of Closure
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    Chapter 24 Recovering Localized Adversarial Attacks
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    Chapter 25 On the Interpretation of Recurrent Neural Networks as Finite State Machines
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    Chapter 26 Neural Field Model for Measuring and Reproducing Time Intervals
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    Chapter 27 Widely Linear Complex-Valued Autoencoder: Dealing with Noncircularity in Generative-Discriminative Models
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    Chapter 28 NatCSNN: A Convolutional Spiking Neural Network for Recognition of Objects Extracted from Natural Images
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    Chapter 29 Deep Semantic Asymmetric Hashing
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    Chapter 30 A Neural Network for Semi-Supervised Learning on Manifolds
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    Chapter 31 Counting with Analog Neurons
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    Chapter 32 On the Bounds of Function Approximations
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    Chapter 33 Probabilistic Bounds for Approximation by Neural Networks
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    Chapter 34 Tree Memory Networks for Sequence Processing
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    Chapter 35 On Deep Set Learning and the Choice of Aggregations
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    Chapter 36 Hilbert Vector Convolutional Neural Network: 2D Neural Network on 1D Data
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    Chapter 37 The Same Size Dilated Attention Network for Keypoint Detection
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    Chapter 38 Gradient-Based Learning of Compositional Dynamics with Modular RNNs
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    Chapter 39 Transfer Learning with Sparse Associative Memories
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    Chapter 40 Linear Memory Networks
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    Chapter 41 A Multi-armed Bandit Algorithm Available in Stationary or Non-stationary Environments Using Self-organizing Maps
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    Chapter 42 Cooperation and Coordination Regimes by Deep Q-Learning in Multi-agent Task Executions
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    Chapter 43 Boosting Reinforcement Learning with Unsupervised Feature Extraction
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    Chapter 44 A Multi-objective Reinforcement Learning Algorithm for JSSP
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    Chapter 45 A Reinforcement Learning Approach for Sequential Spatial Transformer Networks
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    Chapter 46 Deep Recurrent Policy Networks for Planning Under Partial Observability
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    Chapter 47 Mixed-Reality Deep Reinforcement Learning for a Reach-to-grasp Task
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    Chapter 48 FMNet: Multi-agent Cooperation by Communicating with Featured Message Network
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    Chapter 49 Inferring Event-Predictive Goal-Directed Object Manipulations in REPRISE
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    Chapter 50 On Unsupervised Learning of Traversal Cost and Terrain Types Identification Using Self-organizing Maps
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    Chapter 51 Scaffolding Haptic Attention with Controller Gating
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    Chapter 52 Benchmarking Incremental Regressors in Traversal Cost Assessment
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    Chapter 53 CPG Driven RBF Network Control with Reinforcement Learning for Gait Optimization of a Dung Beetle-Like Robot
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    Chapter 54 Training Delays in Spiking Neural Networks
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    Chapter 55 An Izhikevich Model Neuron MOS Circuit for Low Voltage Operation
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    Chapter 56 UAV Detection: A STDP Trained Deep Convolutional Spiking Neural Network Retina-Neuromorphic Approach
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    Chapter 57 Autonomous Learning Paradigm for Spiking Neural Networks
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    Chapter 58 Multi-objective Spiking Neural Network Hardware Mapping Based on Immune Genetic Algorithm
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    Chapter 59 The Importance of Self-excitation in Spiking Neural Networks Evolved to Recognize Temporal Patterns
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    Chapter 60 Estimating and Factoring the Dropout Induced Distribution with Gaussian Mixture Model
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    Chapter 61 Sequence Disambiguation with Synaptic Traces in Associative Neural Networks
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    Chapter 62 Robust Optimal-Size Implementation of Finite State Automata with Synfire Ring-Based Neural Networks
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    Chapter 63 A Neural Circuit Model of Adaptive Robust Tracking Control for Continuous-Time Nonlinear Systems