Regularized Least-Squares for Parse Ranking. - Evgeni Tsivtsivadze; Tapio Pahikkala; Sampo Pyysalo; Jorma Boberg; Aleksandr Mylläri; Tapio Salakoski (IDA, 2005)

Locality-Convolution Kernel and Its Application to Dependency Parse Ranking. - Evgeni Tsivtsivadze; Tapio Pahikkala; Jorma Boberg; Tapio Salakoski (IEA/AIE, 2006)

Locality Kernels for Protein Classification. - Evgeni Tsivtsivadze; Jorma Boberg; Tapio Salakoski (WABI, 2007)

A Sparse Regularized Least-Squares Preference Learning Algorithm. - Evgeni Tsivtsivadze; Tapio Pahikkala; Antti Airola; Jorma Boberg; Tapio Salakoski (SCAI, 2008)

Kernels for Text Analysis. - Evgeni Tsivtsivadze; Tapio Pahikkala; Jorma Boberg; Tapio Salakoski (Advances of Computational Intelligence in Industrial Systems, 2008)

Locality kernels for sequential data and their applications to parse ranking. - Evgeni Tsivtsivadze; Tapio Pahikkala; Jorma Boberg; Tapio Salakoski (Appl. Intell., 2009)

An efficient algorithm for learning to rank from preference graphs. - Tapio Pahikkala; Evgeni Tsivtsivadze; Antti Airola; Jouni Järvinen; Jorma Boberg (Mach. Learn., 2009)

Co-Regularized Least-Squares for Label Ranking. - Evgeni Tsivtsivadze; Tapio Pahikkala; Jorma Boberg; Tapio Salakoski; Tom Heskes (Preference Learning, 2010)

Learning intransitive reciprocal relations with kernel methods. - Tapio Pahikkala; Willem Waegeman; Evgeni Tsivtsivadze; Tapio Salakoski; Bernard De Baets (Eur. J. Oper. Res., 2010)

Multi-output Ranking for Automated Reasoning. - Daniel Kühlwein; Josef Urban; Evgeni Tsivtsivadze; Herman Geuvers; Tom Heskes (KDIR, 2011)

Learning2Reason. - Daniel Kühlwein; Josef Urban; Evgeni Tsivtsivadze; Herman Geuvers; Tom Heskes (Calculemus/MKM, 2011)

Semantic Graph Kernels for Automated Reasoning. - Evgeni Tsivtsivadze; Josef Urban; Herman Geuvers; Tom Heskes (SDM, 2011)

Overview and Evaluation of Premise Selection Techniques for Large Theory Mathematics. - Daniel Kühlwein; Twan van Laarhoven; Evgeni Tsivtsivadze; Josef Urban; Tom Heskes (IJCAR, 2012)

Online Co-regularized Algorithms. - Tom de Ruijter; Evgeni Tsivtsivadze; Tom Heskes (Discovery Science, 2012)

Molecular Machines in the Synapse: Overlapping Protein Sets Control Distinct Steps in Neurosecretion. - L. Niels Cornelisse; Evgeni Tsivtsivadze; Marieke Meijer; Tjeerd Dijkstra; Tom Heskes; Matthijs Verhage (PLoS Comput. Biol., 2012)

Online semi-supervised learning: Algorithm and application in metagenomics. - Sultan Imangaliyev; Bart Keijser; Wim Crielaard; Evgeni Tsivtsivadze (BIBM, 2013)

Multi-view Multi-class Classification for Identification of Pathogenic Bacterial Strains. - Evgeni Tsivtsivadze; Tom Heskes; Armand Paauw (MCS, 2013)

Neighborhood Co-regularized Multi-view Spectral Clustering of Microbiome Data. - Evgeni Tsivtsivadze; Hanneke Borgdorff; Janneke van de Wijgert; Frank H. J. Schuren; Rita Verhelst; Tom Heskes (PSL, 2013)

Semi-supervised Ranking Pursuit. - Evgeni Tsivtsivadze; Tom Heskes (CoRR, 2013)

Personalized microbial network inference via co-regularized spectral clustering. - Sultan Imangaliyev; Bart Keijser; Wim Crielaard; Evgeni Tsivtsivadze (BIBM, 2014)

Premise Selection for Mathematics by Corpus Analysis and Kernel Methods. - Jesse Alama; Tom Heskes; Daniel Kühlwein; Evgeni Tsivtsivadze; Josef Urban (J. Autom. Reason., 2014)