Artificial Neural Networks and Machine Learning - ICANN 2020

Reinforcement Learning II.- GAN-based Planning Model in Deep Reinforcement Learning.- Guided Reinforcement Learning via Sequence Learning.- Neural Machine Translation based on Improved Actor-Critic Method.- Neural Machine Translation based on Prioritized Experience Replay.- Improving Multi-Agent Reinforcement Learning with Imperfect Human Knowledge.- Reinforcement Learning III.- Adaptive Skill Acquisition in Hierarchical Reinforcement Learning.- Social Navigation with Human Empowerment driven Deep Reinforcement Learning.- Curious Hierarchical Actor-Critic Reinforcement Learning.- Policy Entropy for Out-of-Distribution Classification.- Reservoir Computing.- Analysis of reservoir structure contributing to robustness against structural failure of Liquid State Machine.- Quantifying robustness and capacity of reservoir computers with consistency profiles.- Two-Step FORCE Learning Algorithm for Fast Convergence in Reservoir Computing.- Morphological Computation of Skin Focusing on Fingerprint Structure.- Time Series Clustering with Deep Reservoir Computing.- ReservoirPy: an Efficient and User-Friendly Library to Design Echo State Networks.- Robotics and Neural Models of Perception and Action.- Adaptive, Neural Robot Control - Path Planning on 3D Spiking Neural Networks.- CABIN: A Novel Cooperative Attention Based Location Prediction Network Using Internal-External Trajectory Dependencies.- Neuro-Genetic Visuomotor Architecture for Robotic Grasping.- From Geometries to Contact Graphs.- Sentiment Classification.- Structural Position Network for Aspect-based Sentiment Classification.- Cross-Domain Sentiment Classification using Topic Attention and Dual-Task Adversarial Training.- Data Augmentation for Sentiment Analysis in English - the Online Approach.- Spiking Neural Networks I.- Dendritic computation in a point neuron model..- Benchmarking Deep Spiking Neural Networks on Neuromorphic Hardware.- Unsupervised Learning of Spatio-Temporal Receptive Fields from an Event-Based Vision Sensor.- Spike-Train Level Unsupervised Learning Algorithm for Deep Spiking Belief Networks.- Spiking Neural Networks II.- Modelling Neuromodulated Information Flow and Energetic Consumption at Thalamic Relay Synapses.- Learning Precise Spike Timings with Eligibility Traces.- Meta-STDP rule stabilizes synaptic weights under in vivo-like ongoing spontaneous activity in a computational model of CA1 pyramidal cell.- Adaptive Chemotaxis for improved Contour Tracking using Spiking Neural Networks.- Text Understanding I.- Mental Imagery-Driven Neural Network to Enhance Representation for Implicit Discourse Relation Recognition.- Adaptive Convolution Kernel for Text Classification via Multi-Channel Representations.- Text generation in discrete space.- Short text processing for analyzing user portraits: A dynamic combination.- Text Understanding II.- A Hierarchical Fine-Tuning Approach Based on Joint Embedding of Words and Parent Categories forHierarchical Multi-label Text Classification.- Boosting Tricks for Word Mover's Distance.- Embedding Compression with Right Triangle Similarity Transformations.- Neural Networks for Detecting Irrelevant Questions during Visual Question Answering.- F-Measure Optimisation and Label Regularisation for Energy-based Neural Dialogue State Tracking Models.- Unsupervised Learning.- Unsupervised Change Detection using Joint Autoencoders for Age-Related Macular Degeneration Progression.- A fast algorithm to find Best Matching Units in Self-Organizing Maps.- Tumor Characterization using Unsupervised Learning of Mathematical Relations within Breast Cancer Data.- Balanced SAM-kNN: Online Learning with Heterogeneous Drift and Imbalanced Data.- A Rigorous Link Between Self-Organizing Maps and Gaussian Mixture Models.- Collaborative Clustering through Optimal Transport.