Neural Information Processing: 26th International Conference, ICONIP 2019, Sydney, NSW, Australia, December 12-15, 2019, Proceedings, Part III

by Tom Gedeon, Kok Wai Wong, Minho Lee

Overview

The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019.

The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 11955, is organized in topical sections on semantic and graph based approaches; spiking neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models.

Product Details

ISBN-13:	9783030367176
Publisher:	Springer International Publishing
Publication date:	12/11/2019
Series:	Lecture Notes in Computer Science , #11955
Edition description:	1st ed. 2019
Pages:	649
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Semantic and Graph Based Approaches.- GL2vec: Graph Embedding Enriched by Line graphs with Edge Features.- Joint Semantic Hashing using Deep Supervised and Unsupervised Methods.- Label-Based Deep Semantic Hashing for Cross-Modal Retrieval.- HRec: Heterogeneous Graph Embedding-Based Personalized Point-of-Interest Recommendation.- Embedding and Predicting Software Security Entity Relationships: A Knowledge Graph Based Approach.- SACIC: A Semantics-aware Convolutional Image Captioner using Multi-Level Pervasive Attention.- One Analog Neuron Cannot Recognize Deterministic Context-Free Languages.- Tag-based Semantic Features for Scene Image Classification.- Integrating TM Knowledge into NMT with Double Chain Graph.- Learning Transferable Policies with Improved Graph Neural Networks on Serial Robotic Structure.- Visualizing Readable Instance Graphs of Ontology with Memo Graph.- Spiking Neuron and Related Models.- Hippocampus Segmentation in MRI Using Side U-Net Model.- AutoMLfor DenseNet Compression.- Mechanisms of Reward-Modulated STDP and Winner-Take-All in Bayesian Spiking Decision-Making Circuit.- Homeostasis-based CNN-to-SNN Conversion of Inception and Residual Architectures.- Training Large-Scale Spiking Neural Networks on Multi-core Neuromorphic System Using Backpropagation.- Deep learning of EEG Data in the NeuCube Brain-inspired Spiking Neutral Network Architecture for a Better Understanding of Depression.- Text Computing Using Neural Techniques.- Watch and Ask: Video Question Generation.- Multi-Perspective Denoising Reader for Multi-Paragraph Reading Comprehension.- Models in the Wild: On Corruption Robustness of Neural NLP Systems.- Hie-Transformer: A Hierarchical Hybrid Transformer for Abstractive Article Summarization.- Target-Based Attention Model for Aspect-Level Sentiment Analysis.- Keyphrase Generation with Word Attention.- Dynamic Neural Language Models.- A Fast Convolutional Self-attention Based Speech Dereverberation Method forRobust Speech Recognition.- Option Attentive Capsule Network for Multi-choice Reading Comprehension.- Exploring and Identifying Malicious Sites in Dark Web Using Machine Learning.- Paragraph-Level Hierarchical Neural Machine Translation.- Residual Connection-based Multi-step Reasoning via Commonsense Knowledge for Multiple Choice Machine Reading Comprehension.- Zero-Shot Transfer Learning Based on Visual and Textual Resemblance.- Morphological Knowledge Guided Mongolian Constituent Parsing.- BERT based Hierarchical Sequence Classification for Context-aware Microblog Sentiment Analysis.- Topic Aware Context Modelling for Conversation Response Generation.- What a Dialogue! A Deep Neural Framework for Contextual Affect Detection.- Improving student forum responsiveness: Detecting Duplicate Questions in Educational Forums.- Time-series and Related Models.- On Probability Calibration of Recurrent Text Recognition Network.- On the Hermite Series-Based Generalized Regression Neural Networks for Stream Data Mining.- Deep Hybrid Spatiotemporal networks for Continuous Pain Intensity Estimation.- Sales Demand Forecast in E-commerce using a Long Short-Term Memory Neural Network Methodology.- Deep Point-wise Prediction for Action Temporal Proposal.- Real-time Financial Data Prediction Using Meta-cognitive Recurrent Kernel Online Sequential Extreme Learning Machine.- Deep Spatial-Temporal Field for Human Head Orientation Estimation.- Prediction-Coherent LSTM-based Recurrent Neural Network for Safer Glucose Predictions in Diabetic People.- Teacher-Student Learning and Post-Processing for Robust BiLSTM Mask-Based Acoustic Beamforming.- Maxout into MDLSTM for offline Arabic handwriting recognition.- Unsupervised Neural Models.- Unsupervised Feature Selection Based on Matrix Factorization with Redundancy Minimization.- Distance estimation for Quantum Prototypes based Clustering.- Accelerating Bag-of-Words with SOM.- A Deep Clustering-Guide Learning for Unsupervised Person Re-identification.- Semi-Supervised Deep Learning Using Unsupervised Discriminant Projection.- Unsupervised pre-training of the brain connectivity dynamic using residual D-net.- Clustering Ensemble Selection with Determinantal Point Processes.- Generative Histogram-based Model using Unsupervised Learning.