Evgeni Tsivtsivadze

23 papers A 2B 2C 2Journal 7Unranked 7
YearRankTypeTitle / Venue / Authors
2014 — conf
Personalized microbial network inference via co-regularized spectral clustering.
BIBM
Sultan Imangaliyev, Bart Keijser, Wim Crielaard, Evgeni Tsivtsivadze
2014 J jnl
Premise Selection for Mathematics by Corpus Analysis and Kernel Methods.
J. Autom. Reason.
Jesse Alama, Tom Heskes, Daniel Kühlwein, Evgeni Tsivtsivadze, Josef Urban
2013 — conf
Multi-view Multi-class Classification for Identification of Pathogenic Bacterial Strains.
MCS
Evgeni Tsivtsivadze, Tom Heskes, Armand Paauw
2013 — conf
Neighborhood Co-regularized Multi-view Spectral Clustering of Microbiome Data.
PSL
Evgeni Tsivtsivadze, Hanneke Borgdorff, Janneke van de Wijgert, Frank H. J. Schuren, Rita Verhelst, Tom Heskes
2013 — conf
Online semi-supervised learning: Algorithm and application in metagenomics.
BIBM
Sultan Imangaliyev, Bart Keijser, Wim Crielaard, Evgeni Tsivtsivadze
2013 J jnl
Semi-supervised Ranking Pursuit.
CoRR
Evgeni Tsivtsivadze, Tom Heskes
2012 J jnl
Molecular Machines in the Synapse: Overlapping Protein Sets Control Distinct Steps in Neurosecretion.
PLoS Comput. Biol.
L. Niels Cornelisse, Evgeni Tsivtsivadze, Marieke Meijer, Tjeerd Dijkstra, Tom Heskes, Matthijs Verhage
2012 B conf
Online Co-regularized Algorithms.
Discovery Science
Tom de Ruijter, Evgeni Tsivtsivadze, Tom Heskes
2012 A conf
Overview and Evaluation of Premise Selection Techniques for Large Theory Mathematics.
IJCAR
Daniel Kühlwein, Twan van Laarhoven, Evgeni Tsivtsivadze, Josef Urban, Tom Heskes
2011 — conf
Learning2Reason.
Calculemus/MKM
Daniel Kühlwein, Josef Urban, Evgeni Tsivtsivadze, Herman Geuvers, Tom Heskes
2011 — conf
Multi-output Ranking for Automated Reasoning.
KDIR
Daniel Kühlwein, Josef Urban, Evgeni Tsivtsivadze, Herman Geuvers, Tom Heskes
2011 J jnl
Premise Selection for Mathematics by Corpus Analysis and Kernel Methods
CoRR
Jesse Alama, Daniel Kühlwein, Evgeni Tsivtsivadze, Josef Urban, Tom Heskes
2011 A conf
Semantic Graph Kernels for Automated Reasoning.
SDM
Evgeni Tsivtsivadze, Josef Urban, Herman Geuvers, Tom Heskes
2010 — ch.
Co-Regularized Least-Squares for Label Ranking.
Preference Learning
Evgeni Tsivtsivadze, Tapio Pahikkala, Jorma Boberg, Tapio Salakoski, Tom Heskes
2010 J jnl
Learning intransitive reciprocal relations with kernel methods.
Eur. J. Oper. Res.
Tapio Pahikkala, Willem Waegeman, Evgeni Tsivtsivadze, Tapio Salakoski, Bernard De Baets
2010 — ed.
Pattern Recognition in Bioinformatics - 5th IAPR International Conference, PRIB 2010, Nijmegen, The Netherlands, September 22-24, 2010. Proceedings
PRIB
Tjeerd Dijkstra, Evgeni Tsivtsivadze, Elena Marchiori, Tom Heskes
2009 J jnl
An efficient algorithm for learning to rank from preference graphs.
Mach. Learn.
Tapio Pahikkala, Evgeni Tsivtsivadze, Antti Airola, Jouni Järvinen, Jorma Boberg
2009 J jnl
Locality kernels for sequential data and their applications to parse ranking.
Appl. Intell.
Evgeni Tsivtsivadze, Tapio Pahikkala, Jorma Boberg, Tapio Salakoski
2008 — conf
A Sparse Regularized Least-Squares Preference Learning Algorithm.
SCAI
Evgeni Tsivtsivadze, Tapio Pahikkala, Antti Airola, Jorma Boberg, Tapio Salakoski
2008 — ch.
Kernels for Text Analysis.
Advances of Computational Intelligence in Industrial Systems
Evgeni Tsivtsivadze, Tapio Pahikkala, Jorma Boberg, Tapio Salakoski
2007 C conf
Locality Kernels for Protein Classification.
WABI
Evgeni Tsivtsivadze, Jorma Boberg, Tapio Salakoski
2006 C conf
Locality-Convolution Kernel and Its Application to Dependency Parse Ranking.
IEA/AIE
Evgeni Tsivtsivadze, Tapio Pahikkala, Jorma Boberg, Tapio Salakoski
2005 B conf
Regularized Least-Squares for Parse Ranking.
IDA
Evgeni Tsivtsivadze, Tapio Pahikkala, Sampo Pyysalo, Jorma Boberg, Aleksandr Mylläri, Tapio Salakoski