Applications
Automated Grading of Exam Responses: An Extensive Classification Benchmark
Automatic human-like detection of code smells
HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM
Predicting reach to find persuadable customers: improving uplift models for churn prevention
Classification
A Semi-Supervised Framework for Misinformation Detection
An Analysis of Performance Metrics for Imbalanced Classification
Combining Predictions under Uncertainty: The Case of Random Decision Trees
Shapley-Value Data Valuation for Semi-Supervised Learning
Data streams
A Network Intrusion Detection System for Concept Drifting Network Traffic Data
Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams
Statistical Analysis of Pairwise Connectivity
Graph and Network Mining
FHA: Fast Heuristic Attack against Graph Convolutional Networks
Ranking Structured Objects with Graph Neural Networks
Machine Learning for COVID-19
Knowledge discovery of the delays experienced in reporting covid19 confirmed positive cases using time to event models
Multi-Scale Sentiment Analysis of Location-Enriched COVID-19 Arabic Social Data
Prioritization of COVID-19 literature via unsupervised keyphrase extraction and document representation learning
Sentiment Nowcasting during the COVID-19 Pandemic
Neural Networks and Deep Learning
A Sentence-level Hierarchical BERT Model for Document Classification with Limited Labelled Data
Calibrated Resampling for Imbalance and Long-Tails in Deep learning
Consensus Based Vertically Partitioned Multi-Layer Perceptrons for Edge Computing
Controlling BigGAN Image Generation with a Segmentation Network
GANs for tabular healthcare data generation: a review on utility and privacy
Preferences and Recommender Systems
An Ensemble Hypergraph Learning framework for Recommendation
KATRec: Knowledge Aware aTtentive Sequential Recommendations
Representation Learning and Feature Selection
Elliptical Ordinal Embedding
Unsupervised Feature Ranking via Attribute Networks
Responsible Artificial Intelligence
Deriving a Single Interpretable Model by Merging Tree-based Classifiers
Ensemble of Counterfactual Explainers. Riccardo Guidotti and Salvatore Ruggieri
Learning Time Series Counterfactuals via Latent Space Representations
Leveraging Grad-CAM to Improve the Accuracy of Network Intrusion Detection Systems
Local Interpretable Classifier Explanations with Self-generated Semantic Features
Privacy risk assessment of individual psychometric profiles
The Case for Latent Variable vs Deep Learning Methods in Misinformation Detection: An Application to COVID-19
Spatial, Temporal and Spatiotemporal Data
Local Exceptionality Detection in Time Series Using Subgroup Discovery
Neural Additive Vector Autoregression Models for Causal Discovery in Time Series
Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data.