Attention in Recurrent Neural Networks for Energy Disaggregation
Nikolaos Virtsionis Gkalinikis, Christoforos Nalmpantis and Dimitris Vrakas
Constrained Clustering via Post-Processing
Nguyen Viet Dung Nghiem, Christel Vrain, Thi-Bich-Hanh Dao and Ian Davidson
COVID-19 therapy target discovery with context-aware literature mining
Matej Martinc, Blaž Škrlj, Sergej Pirkmajer, Nada Lavrač, Bojan Cestnik, Martin Marzidovšek and Senja Pollak
Evaluating Decision Makers over Selectively Labelled Data: A Causal Modelling Approach
Riku Laine, Antti Hyttinen and Michael Mathioudakis
Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars
Orestis Lampridis, Riccardo Guidotti and Salvatore Ruggieri
Extreme Algorithm Selection with Dyadic Feature Representation
Alexander Tornede, Marcel Wever and Eyke Hüllermeier
Extreme Gradient Boosted Multi-label Trees for Dynamic Classifier Chains
Simon Bohlender, Eneldo Loza Mencía and Moritz Kulessa
FABBOO – Online Fairness-aware Learning under Class Imbalance
Vasileios Iosifidis and Eirini Ntoutsi
FEAT: A Fairness-enhancing and Concept-adapting Decision Tree Classifier
Wenbin Zhang and Albert Bifet
Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology
Oghenejokpeme Orhobor, Joseph French, Larisa Soldatova and Ross King
Improving deep unsupervised anomaly detection by exploiting VAE latent space distribution
Fabrizio Angiulli, Fabio Fassetti and Luca Ferragina
Interpretable Machine Learning with Bitonic Generalized Additive Models and Automatic Feature Construction
Noëlie Cherrier, Michael Mayo, Jean-Philippe Poli, Maxime Defurne and Franck Sabatié
Iterative Multi-Mode Discretization: Applications to Co-Clustering
Hadi Fanaee-T and Magne Thoresen
Learning surrogates of a radiative transfer model for the Sentinel 5P satellite
Jure Brence, Jovan Tanevski, Jennifer Adams, Edward Malina and Sašo Džeroski
Maximizing Network Coverage Under the Presence of Time Constraint by Injecting Most Effective k-Links
Kouzou Ohara, Takayasu Fushimi, Kazumi Saito, Masahiro Kimura and Hiroshi Motoda
Mining Constrained Regions of Interest: An Optimization Approach
Alexandre Dubray, Guillaume Derval, Pierre Schaus and Siegfried Nijssen
Missing value imputation with MERCS: a faster alternative to MissForest when retraining is infeasible
Elia Van Wolputte and Hendrik Blockeel
Mitigating Discrimination in Clinical Machine Learning Decision Support using Algorithmic Processing Techniques
Emma Briggs and Jaakko Hollmén
Multi-Directional Rule Set Learning
Jonas Schouterden, Jesse Davis and Hendrik Blockeel
Nets versus trees for feature ranking and gene network inference
Nicolas Vecoven, Jean-Michel Begon, Antonio Sutera, Pierre Geurts and Vân Anh Huynh-Thu
On Aggregation in Ensembles of Multilabel Classifiers
Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía and Johannes Fürnkranz
One-Class Ensembles for Rare Genomic Sequences Identification
Jonathan Kaufmann, Kathryn Asalone, Roberto Corizzo, Colin Saldanha, John Bracht and Nathalie Japkowicz
Pathway Activity Score Learning for Dimensionality Reduction of Gene Expression Data
Ioulia Karagiannaki, Yannis Pantazis, Ekaterini Chatzaki and Ioannis Tsamardinos
Simultaneous Process Drift Detection and Characterization with Pattern-based Change Detectors
Angelo Impedovo, Paolo Mignone, Corrado Loglisci and Michelangelo Ceci
Spatiotemporal Traffic Anomaly Detection on Urban Road Network Using Tensor Decomposition Method
Leo Tišljarić, Sofia Fernandes, Tonči Carić and João Gama
Unsupervised Concept Drift Detection using a Student–Teacher Approach
Vitor Cerqueira, Heitor Gomes and Albert Bifet
Short Papers
Assembled Feature Selection For Credit Scoring in Microfinance With Non-Traditional Features
Saulo Carpio, Pedro Gomes, Luis Rodrigues and João Gama
Balancing between scalability and accuracy in time-series classification for stream and batch settings
Apostolos Glenis and George Vouros
Hierarchy decomposition pipeline: A toolbox for comparison of model induction algorithms on hierarchical multi-label classification problems
Vedrana Vidulin and Sašo Džeroski
DeCStor: A Framework for Privately and Securely Sharing Files Using a Public Blockchain
Maria Siopi, George Vlahavas, Kostas Karassavas and Athena Vakali
Deep Convolutional Embedding for Painting Clustering: Case Study on Picasso’s Artworks
Giovanna Castellano and Gennaro Vessio
Detecting Temporal Anomalies in Business Processes using Distance-based Methods
Ioannis Mavroudopoulos and Anastasios Gounaris
Dynamic Incremental Semi-Supervised Fuzzy Clustering for Bipolar Disorder Episode Prediction
Gabriella Casalino, Giovanna Castellano, Francesco Galetta and Katarzyna Kaczmarek-Majer
Enhanced food safety through Deep Learning for food recalls prediction
Georgios Makridis, Philip Mavrepis, Dimosthenis Kyriazis, Ioanna Polychronou and Stathis Kaloudis
FairNN – Conjoint Learning of Fair Representations for Fair Decisions
Tongxin Hu, Vasileios Iosifidis, Wentong Liao, Hang Zhang, Michael Ying Yang, Eirini Ntoutsi and Bodo Rosenhahn
Federated Ensemble Regression using Classification
Oghenejokpeme Orhobor, Larisa Soldatova and Ross King
Investigating parallelization of MAML
Jan Bollenbacher, Florian Soulier, Beate Rhein and Laurenz Wiskott
Mining Disjoint Sequential Pattern Pairs from Tourist Trajectory Data
Siqi Peng and Akihiro Yamamoto
On the utilization of structural and textual information of a scientific knowledge graph to discover future research collaborations: a link prediction perspective
Nikolaos Giarelis, Nikos Kanakaris and Nikos Karacapilidis
Predicting and Explaining Privacy Risk Exposure in Mobility Data
Francesca Naretto, Roberto Pellungrini, Anna Monreale, Franco Maria Nardini and Mirco Musolesi
Predicting the Health Condition of mHealth App Users with Large Differences in the Amount of Recorded Observations – Where to Learn from?
Vishnu Unnikrishnan, Yash Shah, Miro Schleicher, Mirela Strandzheva, Plamen Dimitrov, Doroteya Velikova, Ruediger Pryss, Johannes Schobel, Winfried Schlee and Myra Spiliopoulou
Semantic annotation of predictive modelling experiments
Ilin Tolovski, Sašo Džeroski and Panče Panov
Semantic description of data mining datasets: An ontology-based annotation schema
Ana Kostovska, Sašo Džeroski and Panče Panov
Time Series Regression in Professional Road Cycling
Arie-Willem de Leeuw, Mathieu Heijboer, Mathijs Hofmijster, Stephan van der Zwaard and Arno Knobbe
WeakAL: Combining Active Learning and Weak Supervision
Julius Gonsior, Maik Thiele and Wolfgang Lehner
