Artificial neural networks and machine learning -- ICANN 2020 : 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15-18, 2020, Proceedings. Part II / Igor Farkaš, Paolo Masulli, Stefan Wermter (eds.).

Model Compression I
Fine-grained Channel Pruning for Deep Residual Neural Networks
A Lightweight Fully Convolutional Neural Network of High Accuracy Surface Defect Detection
Detecting Uncertain BNN Outputs on FPGA Using Monte Carlo Dropout Sampling
Neural network compression via learnable wavelet transforms
Fast and Robust Compression of Deep Convolutional Neural Networks
Model Compression II
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima
Log-Nets: Logarithmic Feature-Product Layers Yield More Compact Networks
Tuning Deep Neural Network's hyperparameters constrained to deployability on tiny systems
Obstacles to Depth Compression of Neural Networks
Multi-task and Multi-label Learning
Multi-Label Quadruplet Dictionary Learning
Pareto Multi-Task Deep Learning
Convex Graph Laplacian Multi-Task Learning SVM
Neural Network Theory and Information Theoretic Learning
Prediction Stability as a Criterion in Active Learning
Neural Spectrum Alignment: Empirical Study
Nonlinear, Nonequilibrium Landscape Approach to Neural Network Dynamics
Hopfield Networks for Vector Quantization
Prototype-Based Online Learning on Homogeneously Labeled Streaming Data
Normalization and Regularization Methods
Neural Network Training with Safe Regularization in the Null Space of Batch Activations
The Effect of Batch Normalization in the Symmetric Phase
Regularized Pooling
Reinforcement Learning I
Deep Recurrent Deterministic Policy Gradient for Physical Control
Exploration via Progress-Driven Intrinsic Rewards
An improved reinforcement learning based heuristic dynamic programming algorithm for model-free optimal control
PBCS: Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning
Understanding failures of deterministic actor-critic with continuous action spaces and sparse rewards
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 for Hierarchical 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.