Neural Information Processing

Table of Contents

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   Book Overview
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   Chapter 1 fMRI Semantic Category Decoding Using Linguistic Encoding of Word Embeddings
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   Chapter 2 Named Entity Disambiguation via Probabilistic Graphical Model with Embedding Features
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   Chapter 3 Category-Embodied Knowledge Embedding
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   Chapter 4 Unsupervised Ensemble Learning Based on Graph Embedding for Image Clustering
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   Chapter 5 Potential Probability of Negative Triples in Knowledge Graph Embedding
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   Chapter 6 Event Causality Identification by Modeling Events and Relation Embedding
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   Chapter 7 Topic-Bigram Enhanced Word Embedding Model
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   Chapter 8 Hybridized Character-Word Embedding for Korean Traditional Document Translation
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    Chapter 9 Word Embedding Based on Low-Rank Doubly Stochastic Matrix Decomposition
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    Chapter 10 Meta-path Based Heterogeneous Graph Embedding for Music Recommendation
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    Chapter 11 Knowledge Graph Embedding via Entities’ Type Mapping Matrix
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    Chapter 12 A Sentence Similarity Model Based on Word Embeddings and Dependency Syntax-Tree
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    Chapter 13 Semi-coupled Transform Learning
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    Chapter 14 A Refined Spatial Transformer Network
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    Chapter 15 Convolutional Transform Learning
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    Chapter 16 Delving into Diversity in Substitute Ensembles and Transferability of Adversarial Examples
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    Chapter 17 Transfer Learning Using Progressive Neural Networks and NMT for Classification Tasks in NLP
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    Chapter 18 Deep Transfer Learning via Minimum Enclosing Balls
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    Chapter 19 Cross-domain Recommendation with Probabilistic Knowledge Transfer
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    Chapter 20 Transfer Learning with Active Queries for Relational Data Modeling Across Multiple Information Networks
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    Chapter 21 Semi-supervised Transfer Metric Learning with Relative Constraints
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    Chapter 22 Fuzzy Domain Adaptation Using Unlabeled Target Data
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    Chapter 23 Reinforcement Learning Policy with Proportional-Integral Control
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    Chapter 24 Data-Efficient Reinforcement Learning Using Active Exploration Method
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    Chapter 25 Averaged-A3C for Asynchronous Deep Reinforcement Learning
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    Chapter 26 Deep Reinforcement Learning for Multi-resource Cloud Job Scheduling
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    Chapter 27 Accelerating Spatio-Temporal Deep Reinforcement Learning Model for Game Strategy
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    Chapter 28 ASD: A Framework for Generation of Task Hierarchies for Transfer in Reinforcement Learning
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    Chapter 29 Driving Control with Deep and Reinforcement Learning in The Open Racing Car Simulator
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    Chapter 30 An Adaptive Box-Normalization Stock Index Trading Strategy Based on Reinforcement Learning
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    Chapter 31 Heterogeneous Multi-task Learning of Evaluation Functions for Chess and Shogi
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    Chapter 32 Reinforcement Learning Based Dialogue Management Strategy
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    Chapter 33 A Family of Maximum Margin Criterion for Adaptive Learning
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    Chapter 34 Multi-task Manifold Learning Using Hierarchical Modeling for Insufficient Samples
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    Chapter 35 Enhanced Metric Learning via Dempster-Shafer Evidence Theory
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    Chapter 36 InsightGAN: Semi-Supervised Feature Learning with Generative Adversarial Network for Drug Abuse Detection
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    Chapter 37 Sparse Feature Learning Using Ensemble Model for Highly-Correlated High-Dimensional Data
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    Chapter 38 Task and Instance Quadratic Ordering for Active Online Multitask Learning
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    Chapter 39 Learning from Titles to Recommend Keywords for Academic Papers
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    Chapter 40 Zero-Shot Learning with Superclasses
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    Chapter 41 Active Learning Methods with Deep Gaussian Processes
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    Chapter 42 Transductive Learning with String Kernels for Cross-Domain Text Classification
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    Chapter 43 Overcoming Catastrophic Forgetting with Self-adaptive Identifiers
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    Chapter 44 Learning, Storing, and Disentangling Correlated Patterns in Neural Networks
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    Chapter 45 MultNet: An Efficient Network Representation Learning for Large-Scale Social Relation Extraction
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    Chapter 46 Geometrical Formulation of the Nonnegative Matrix Factorization
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    Chapter 47 Information Geometric Perspective of Modal Linear Regression
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    Chapter 48 Learning from Audience Intelligence: Dynamic Labeled LDA Model for Time-Sync Commented Video Tagging
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    Chapter 49 Accurate Q-Learning
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    Chapter 50 Monotonicity Extraction for Monotonic Bayesian Networks Parameter Learning
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    Chapter 51 Dynamic Maintenance of Decision Rules for Decision Attribute Values’ Changing
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    Chapter 52 Label Distribution Learning Based on Ensemble Neural Networks
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    Chapter 53 Neural Information Processing in Hierarchical Prototypical Networks
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    Chapter 54 Regularized Tensor Learning with Adaptive One-Class Support Vector Machines
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    Chapter 55 Semi-supervised Multi-label Dimensionality Reduction via Low Rank Representation
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    Chapter 56 Visualization Method of Viewpoints Latent in a Dataset
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    Chapter 57 Localized Multiple Sources Self-Organizing Map
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    Chapter 58 Heterogeneous Dyadic Multi-task Learning with Implicit Feedback
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    Chapter 59 Parallel Cooperative Ensemble Learning by Adaptive Data Weighting and Error-Correcting Output Codes