Lavrač, Nada

26 publications

MLJ 2025 HorNets: Learning from Discrete and Continuous Signals with Routing Neural Networks Boshko Koloski, Nada Lavrac, Blaz Skrlj

MLJ 2022 ReliefE: Feature Ranking in High-Dimensional Spaces via Manifold Embeddings Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic

MLJ 2021 autoBOT: Evolving Neuro-Symbolic Representations for Explainable Low Resource Text Classification Blaz Skrlj, Matej Martinc, Nada Lavrac, Senja Pollak

MLJ 2020 Embedding-Based Silhouette Community Detection Blaz Skrlj, Jan Kralj, Nada Lavrac

MLJ 2020 Propositionalization and Embeddings: Two Sides of the Same Coin Nada Lavrac, Blaz Skrlj, Marko Robnik-Sikonja

JMLR 2019 NetSDM: Semantic Data Mining with Network Analysis Jan Kralj, Marko Robnik-Sikonja, Nada Lavrac

MLJ 2016 Explaining Mixture Models Through Semantic Pattern Mining and Banded Matrix Visualization Prem Raj Adhikari, Anze Vavpetic, Jan Kralj, Nada Lavrac, Jaakko Hollmén

ECML-PKDD 2014 Propositionalization Online Nada Lavrac, Matic Perovsek, Anze Vavpetic

ECML-PKDD 2013 ViperCharts: Visual Performance Evaluation Platform Borut Sluban, Nada Lavrac

ECML-PKDD 2012 ClowdFlows: A Cloud Based Scientific Workflow Platform Janez Kranjc, Vid Podpecan, Nada Lavrac

JMLR 2009 Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining Petra Kralj Novak, Nada Lavrač, Geoffrey I. Webb

JMLR 2008 Closed Sets for Labeled Data Gemma C. Garriga, Petra Kralj, Nada Lavrač

MLJ 2006 Propositionalization-Based Relational Subgroup Discovery with RSD Filip Zelezný, Nada Lavrac

MLJ 2004 Decision Support Through Subgroup Discovery: Three Case Studies and the Lessons Learned Nada Lavrac, Bojan Cestnik, Dragan Gamberger, Peter A. Flach

MLJ 2004 Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving Nada Lavrac, Hiroshi Motoda, Tom Fawcett, Robert Holte, Pat Langley, Pieter W. Adriaans

JMLR 2004 Subgroup Discovery with CN2-SD Nada Lavrač, Branko Kavšek, Peter Flach, Ljupčo Todorovski

ICML 2002 Descriptive Induction Through Subgroup Discovery: A Case Study in a Medical Domain Dragan Gamberger, Nada Lavrac

JAIR 2002 Expert-Guided Subgroup Discovery: Methodology and Application Dragan Gamberger, Nada Lavrac

ECML-PKDD 2001 Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reduction Branko Kavsek, Nada Lavrac, Anuska Ferligoj

ICML 1999 Experiments with Noise Filtering in a Medical Domain Dragan Gamberger, Nada Lavrac, Ciril Groselj

ECML-PKDD 1997 Conditions for Occam's Razor Applicability and Noise Elimination Dragan Gamberger, Nada Lavrac

ALT 1996 Cost-Sensitive Feature Reduction Applied to a Hybrid Genetic Algorithm Nada Lavrac, Dragan Gamberger, Peter D. Turney

ALT 1996 Noise Elimination in Inductive Concept Learning: A Case Study in Medical Diagnosois Dragan Gamberger, Nada Lavrac, Saso Dzeroski

IJCAI 1993 Multiple Predicate Learning Luc De Raedt, Nada Lavrac, Saso Dzeroski

ICML 1991 Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL Saso Dzeroski, Nada Lavrac

AAAI 1986 The Multi-Purpose Incremental Learning System AQ15 and Its Testing Application to Three Medical Domains Ryszard S. Michalski, Igor Mozetic, Jiarong Hong, Nada Lavrac