An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. - Eneldo Loza Mencía; Johannes Fürnkranz (LWA, 2007)

Pairwise learning of multilabel classifications with perceptrons. - Eneldo Loza Mencía; Johannes Fürnkranz (IJCNN, 2008)

Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain. - Eneldo Loza Mencía; Johannes Fürnkranz (ECML/PKDD (2), 2008)

Multilabel classification via calibrated label ranking. - Johannes Fürnkranz; Eyke Hüllermeier; Eneldo Loza Mencía; Klaus Brinker (Mach. Learn., 2008)

Segmentation of legal documents. - Eneldo Loza Mencía (ICAIL, 2009)

Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. - Eneldo Loza Mencía; Johannes Fürnkranz (Semantic Processing of Legal Texts, 2010)

An Evaluation of Multilabel Classification for the Automatic Annotation of Texts. - Eneldo Loza Mencía (LWA, 2010)

Efficient voting prediction for pairwise multilabel classification. - Eneldo Loza Mencía; Sang-Hyeun Park; Johannes Fürnkranz (Neurocomputing, 2010)

Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns. - Wouter Duivesteijn; Eneldo Loza Mencía; Johannes Fürnkranz; Arno J. Knobbe (IDA, 2012)

Using Data Mining on Linked Open Data for Analyzing E-Procurement Information - A Machine Learning approach to the Linked Data Mining Challenge 2013. - Eneldo Loza Mencía; Simon Holthausen; Axel Schulz 001; Frederik Janssen (DMoLD, 2013)

Towards Multilabel Rule Learning. - Eneldo Loza Mencía; Frederik Janssen (LWA, 2013)

Efficient pairwise multilabel classification. - Eneldo Loza Mencía (2013)

Stacking Label Features for Learning Multilabel Rules. - Eneldo Loza Mencía; Frederik Janssen (Discovery Science, 2014)

A Hybrid Multi-strategy Recommender System Using Linked Open Data. - Petar Ristoski; Eneldo Loza Mencía; Heiko Paulheim (SemWebEval@ESWC, 2014)

Graded Multilabel Classification by Pairwise Comparisons. - Christian Brinker; Eneldo Loza Mencía; Johannes Fürnkranz (ICDM, 2014)

Evaluating Multi-label Classification of Incident-related Tweet. - Axel Schulz 001; Eneldo Loza Mencía; Thanh-Tung Dang; Benedikt Schmidt 001 (#MSM, 2014)

Large-Scale Multi-label Text Classification - Revisiting Neural Networks. - Jinseok Nam; Jungi Kim; Eneldo Loza Mencía; Iryna Gurevych; Johannes Fürnkranz (ECML/PKDD (2), 2014)

Simultaneous Feature Selection and Parameter Optimization Using Multi-objective Optimization for Sentiment Analysis. - Mohammed Arif Khan; Asif Ekbal; Eneldo Loza Mencía (ICON, 2015)

Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning. - Jinseok Nam; Eneldo Loza Mencía; Hyunwoo J. Kim; Johannes Fürnkranz (ECML/PKDD (1), 2015)

All-in Text: Learning Document, Label, and Word Representations Jointly. - Jinseok Nam; Eneldo Loza Mencía; Johannes Fürnkranz (AAAI, 2016)

Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization. - Markus Zopf; Eneldo Loza Mencía; Johannes Fürnkranz (COLING, 2016)

Beyond Centrality and Structural Features: Learning Information Importance for Text Summarization. - Markus Zopf; Eneldo Loza Mencía; Johannes Fürnkranz (CoNLL, 2016)

DeepRED - Rule Extraction from Deep Neural Networks. - Jan Ruben Zilke; Eneldo Loza Mencía; Frederik Janssen (DS, 2016)

Using semantic similarity for multi-label zero-shot classification of text documents. - Prateek Veeranna Sappadla; Jinseok Nam; Eneldo Loza Mencía; Johannes Fürnkranz (ESANN, 2016)

Medical Concept Embeddings via Labeled Background Corpora. - Eneldo Loza Mencía; Gerard de Melo; Jinseok Nam (LREC, 2016)

A rapid-prototyping framework for extracting small-scale incident-related information in microblogs: Application of multi-label classification on tweets. - Axel Schulz 001; Eneldo Loza Mencía; Benedikt Schmidt 001 (Inf. Syst., 2016)

Learning rules for multi-label classification: a stacking and a separate-and-conquer approach. - Eneldo Loza Mencía; Frederik Janssen (Mach. Learn., 2016)

Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction. - Camila González; Eneldo Loza Mencía; Johannes Fürnkranz (DS, 2017)

Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification. - Jinseok Nam; Eneldo Loza Mencía; Hyunwoo J. Kim; Johannes Fürnkranz (NIPS, 2017)

Multi-objective Optimisation-Based Feature Selection for Multi-label Classification. - Mohammed Arif Khan; Asif Ekbal; Eneldo Loza Mencía; Johannes Fürnkranz (NLDB, 2017)

Dynamic Classifier Chain with Random Decision Trees. - Moritz Kulessa; Eneldo Loza Mencía (DS, 2018)

Analysis and Optimization of Deep Counterfactual Value Networks. - Patryk Hopner; Eneldo Loza Mencía (KI, 2018)

Which Scores to Predict in Sentence Regression for Text Summarization? - Markus Zopf; Eneldo Loza Mencía; Johannes Fürnkranz (NAACL-HLT, 2018)

Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz (PAKDD (1), 2018)

What's Important in a Text? An Extensive Evaluation of Linguistic Annotations for Summarization. - Markus Zopf; Teresa Botschen; Tobias Falke; Benjamin Heinzerling; Ana Marasovic; Todor Mihaylov; Avinesh P. V. S.; Eneldo Loza Mencía; Johannes Fürnkranz; Anette Frank (SNAMS, 2018)

Analysis and Optimization of Deep CounterfactualValue Networks. - Eneldo Loza Mencía; Patryk Hopner (CoRR, 2018)

Learning Interpretable Rules for Multi-label Classification. - Eneldo Loza Mencía; Johannes Fürnkranz; Eyke Hüllermeier; Michael Rapp (CoRR, 2018)

Improving the Fusion of Outbreak Detection Methods with Supervised Learning. - Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (CIBB, 2019)

Efficient Discovery of Expressive Multi-label Rules Using Relaxed Pruning. - Yannik Klein; Michael Rapp; Eneldo Loza Mencía (DS, 2019)

On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz (DS, 2019)

Learning Context-dependent Label Permutations for Multi-label Classification. - Jinseok Nam; Young-Bum Kim; Eneldo Loza Mencía; Sunghyun Park; Ruhi Sarikaya; Johannes Fürnkranz (ICML, 2019)

Improving Outbreak Detection with Stacking of Statistical Surveillance Methods. - Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (CoRR, 2019)

Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz (CoRR, 2019)

Extreme Gradient Boosted Multi-label Trees for Dynamic Classifier Chains. - Simon Bohlender; Eneldo Loza Mencía; Moritz Kulessa (DS, 2020)

On Aggregation in Ensembles of Multilabel Classifiers. - Vu-Linh Nguyen; Eyke Hüllermeier; Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz (DS, 2020)

Conformal Rule-Based Multi-label Classification. - Eyke Hüllermeier; Johannes Fürnkranz; Eneldo Loza Mencía (KI, 2020)

A Data Set for the Analysis of Text Quality Dimensions in Summarization Evaluation. - Margot Mieskes; Eneldo Loza Mencía; Tim Kronsbein (LREC, 2020)

Learning Gradient Boosted Multi-label Classification Rules. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz; Vu-Linh Nguyen; Eyke Hüllermeier (ECML/PKDD (3), 2020)

Rule-Based Multi-label Classification: Challenges and Opportunities. - Eyke Hüllermeier; Johannes Fürnkranz; Eneldo Loza Mencía; Vu-Linh Nguyen; Michael Rapp (RuleML+RR, 2020)

Learning Structured Declarative Rule Sets - A Challenge for Deep Discrete Learning. - Johannes Fürnkranz; Eyke Hüllermeier; Eneldo Loza Mencía; Michael Rapp (CoRR, 2020)

Sum-Product Networks for Early Outbreak Detection of Emerging Diseases. - Moritz Kulessa; Bennet Wittelsbach; Eneldo Loza Mencía; Johannes Fürnkranz (AIME, 2021)

Combining Predictions Under Uncertainty: The Case of Random Decision Trees. - Florian Busch; Moritz Kulessa; Eneldo Loza Mencía; Hendrik Blockeel (DS, 2021)

Revisiting Non-specific Syndromic Surveillance. - Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (IDA, 2021)

Gradient-Based Label Binning in Multi-label Classification. - Michael Rapp; Eneldo Loza Mencía; Johannes Fürnkranz; Eyke Hüllermeier (ECML/PKDD (3), 2021)

A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance. - Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (Comput., 2021)

Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance. - Michael Rapp; Moritz Kulessa; Eneldo Loza Mencía; Johannes Fürnkranz (Frontiers Big Data, 2021)

Comparing Boosting and Bagging for Decision Trees of Rankings. - Antonella Plaia; Simona Buscemi; Johannes Fürnkranz; Eneldo Loza Mencía (J. Classif., 2022)

A flexible class of dependence-aware multi-label loss functions. - Eyke Hüllermeier; Marcel Wever; Eneldo Loza Mencía; Johannes Fürnkranz; Michael Rapp (Mach. Learn., 2022)

Knowledge Graph Embeddings: Open Challenges and Opportunities. - Russa Biswas; Lucie-Aimée Kaffee; Michael Cochez; Stefania Dumbrava; Theis E. Jendal; Matteo Lissandrini; Vanessa López; Eneldo Loza Mencía; Heiko Paulheim; Harald Sack; Edlira Vakaj; Gerard de Melo (TGDK, 2023)

Tree-based dynamic classifier chains. - Eneldo Loza Mencía; Moritz Kulessa; Simon Bohlender; Johannes Fürnkranz (Mach. Learn., 2023)