Published 2020
Table of Contents:
“...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....
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