Lars Schmidt-Thieme

Krisztian Buza, Alexandros Nanopoulos, Tomás Horváth, Lars Schmidt-Thieme: GRAMOFON: General model-selection framework based on networks. Neurocomputing 75(1): 163-170 (2012)

Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Lars Schmidt-Thieme: Personalized Ranking for Non-Uniformly Sampled Items. Journal of Machine Learning Research - Proceedings Track 18: 231-247 (2012)

Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme: Classification of Sparse Time Series via Supervised Matrix Factorization. AAAI 2012

Ernesto Diaz-Aviles, Lucas Drumond, Zeno Gantner, Lars Schmidt-Thieme, Wolfgang Nejdl: What is happening right now ... that interests me?: online topic discovery and recommendation in twitter. CIKM 2012: 1592-1596

Ruth Janning, Tomás Horváth, Andre Busche, Lars Schmidt-Thieme: GamRec: A Clustering Method Using Geometrical Background Knowledge for GPR Data Preprocessing. AIAI (1) 2012: 347-356

Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme: Invariant Time-Series Classification. ECML/PKDD (2) 2012: 725-740

Ernesto Diaz-Aviles, Lucas Drumond, Lars Schmidt-Thieme, Wolfgang Nejdl: Real-time top-n recommendation in social streams. RecSys 2012: 59-66

Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme: Exploiting the characteristics of matrix factorization for active learning in recommender systems. RecSys 2012: 317-320

Lucas Drumond, Steffen Rendle, Lars Schmidt-Thieme: Predicting RDF triples in incomplete knowledge bases with tensor factorization. SAC 2012: 326-331

Lucas Drumond, Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme: Factorization techniques for student performance classification and ranking. UMAP Workshops 2012

Nguyen Thai-Nghe, Lucas Drumond, Tomás Horváth, Lars Schmidt-Thieme: Using factorization machines for student modeling. UMAP Workshops 2012

Artus Krohn-Grimberghe, Lucas Drumond, Christoph Freudenthaler, Lars Schmidt-Thieme: Multi-relational matrix factorization using bayesian personalized ranking for social network data. WSDM 2012: 173-182

Wolfgang Gaul, Andreas Geyer-Schulz, Lars Schmidt-Thieme, Jonas Kunze (Eds.): Challenges at the Interface of Data Analysis, Computer Science, and Optimization - Proceedings of the 34th Annual Conference of the Gesellschaft für Klassifikation e. V., Karlsruhe, July 21 - 23, 2010. Studies in Classification, Data Analysis, and Knowledge Organization, Springer 2012, isbn 978-3-642-24465-0

Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme: BPR: Bayesian Personalized Ranking from Implicit Feedback. CoRR abs/1205.2618 (2012)

Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme: Active learning for aspect model in recommender systems. CIDM 2011: 162-167

Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme: IQ estimation for accurate time-series classification. CIDM 2011: 216-223

Nguyen Thai-Nghe, Lucas Drumond, Tomás Horváth, Alexandros Nanopoulos, Lars Schmidt-Thieme: Matrix and Tensor Factorization for Predicting Student Performance. CSEDU (1) 2011: 69-78

Artus Krohn-Grimberghe, Andre Busche, Alexandros Nanopoulos, Lars Schmidt-Thieme: Active Learning for Technology Enhanced Learning. EC-TEL 2011: 512-518

Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme: Factorization Models for Forecasting Student Performance. EDM 2011: 11-20

Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme: Fusion of Similarity Measures for Time Series Classification. HAIS (2) 2011: 253-261

Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme, Julia Koller: Fast Classification of Electrocardiograph Signals via Instance Selection. HISB 2011: 9-16

Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme: Personalized Forecasting Student Performance. ICALT 2011: 412-414

Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme: Towards Optimal Active Learning for Matrix Factorization in Recommender Systems. ICTAI 2011: 1069-1076

Timo Reuter, Philipp Cimiano, Lucas Drumond, Krisztian Buza, Lars Schmidt-Thieme: Scalable Event-Based Clustering of Social Media Via Record Linkage Techniques. ICWSM 2011

Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme: A new evaluation measure for learning from imbalanced data. IJCNN 2011: 537-542

Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme: Non-myopic active learning for recommender systems based on Matrix Factorization. IRI 2011: 299-303

Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme: INSIGHT: Efficient and Effective Instance Selection for Time-Series Classification. PAKDD (2) 2011: 149-160

Zeno Gantner, Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme: MyMediaLite: a free recommender system library. RecSys 2011: 305-308

Steffen Rendle, Zeno Gantner, Christoph Freudenthaler, Lars Schmidt-Thieme: Fast context-aware recommendations with factorization machines. SIGIR 2011: 635-644

Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme, Robert Jäschke, Andreas Hotho, Gerd Stumme, Panagiotis Symeonidis: Social Tagging Recommender Systems. Recommender Systems Handbook 2011: 615-644

Nguyen Thai-Nghe, Lucas Drumond, Artus Krohn-Grimberghe, Lars Schmidt-Thieme: Recommender system for predicting student performance. Procedia CS 1(2): 2811-2819 (2010)

Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme: Time-Series Classification Based on Individualised Error Prediction. CSE 2010: 48-54

Artus Krohn-Grimberghe, Alexandros Nanopoulos, Lars Schmidt-Thieme: Integrating OLAP and recommender systems: an evaluation perspective. DOLAP 2010: 85-92

Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme: Individualized Error Estimation for Classification and Regression Models. GfKl 2010: 183-191

Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme: Graph-Based Model-Selection Framework for Large Ensembles. HAIS (1) 2010: 557-564

Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme: Learning Attribute-to-Feature Mappings for Cold-Start Recommendations. ICDM 2010: 176-185

Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme: Cost-sensitive learning methods for imbalanced data. IJCNN 2010: 1-8

Christine Preisach, Leandro Balby Marinho, Lars Schmidt-Thieme: Semi-supervised Tag Recommendation - Using Untagged Resources to Mitigate Cold-Start Problems. PAKDD (1) 2010: 348-357

Bart P. Knijnenburg, Lars Schmidt-Thieme, Dirk G. F. M. Bollen: Workshop on user-centric evaluation of recommender systems and their interfaces. RecSys 2010: 383-384

Steffen Rendle, Lars Schmidt-Thieme: Pairwise interaction tensor factorization for personalized tag recommendation. WSDM 2010: 81-90

Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme: Factorizing personalized Markov chains for next-basket recommendation. WWW 2010: 811-820

Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-Thieme: Swarming to rank for information retrieval. GECCO 2009: 9-16

Avare Stewart, Ernesto Diaz-Aviles, Wolfgang Nejdl, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme: Cross-tagging for personalized open social networking. Hypertext 2009: 271-278

Nguyen Thai-Nghe, Andre Busche, Lars Schmidt-Thieme: Improving Academic Performance Prediction by Dealing with Class Imbalance. ISDA 2009: 878-883

Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme: Learning optimal ranking with tensor factorization for tag recommendation. KDD 2009: 727-736

Steffen Rendle, Christine Preisach, Lars Schmidt-Thieme: Learning to Extract Relations for Relational Classification. PAKDD 2009: 1062-1071

Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme: BPR: Bayesian Personalized Ranking from Implicit Feedback. UAI 2009: 452-461

Zeno Gantner, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme: Optimal Ranking for Video Recommendation. UCMedia 2009: 255-258

Lawrence D. Bergman, Alexander Tuzhilin, Robin D. Burke, Alexander Felfernig, Lars Schmidt-Thieme (Eds.): Proceedings of the 2009 ACM Conference on Recommender Systems, RecSys 2009, New York, NY, USA, October 23-25, 2009. ACM 2009, isbn 978-1-60558-435-5

Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme, Gerd Stumme: Tag recommendations in social bookmarking systems. AI Commun. 21(4): 231-247 (2008)

Christine Preisach, Lars Schmidt-Thieme: Ensembles of relational classifiers. Knowl. Inf. Syst. 14(3): 249-272 (2008)

Krisztian Buza, Lars Schmidt-Thieme: Motif-Based Classification of Time Series with Bayesian Networks and SVMs. GfKl 2008: 105-114

Steffen Rendle, Lars Schmidt-Thieme: Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference. ICDM 2008: 1001-1006

Steffen Rendle, Lars Schmidt-Thieme: Scaling Record Linkage to Non-uniform Distributed Class Sizes. PAKDD 2008: 308-319

Steffen Rendle, Lars Schmidt-Thieme: Online-updating regularized kernel matrix factorization models for large-scale recommender systems. RecSys 2008: 251-258

Karen H. L. Tso-Sutter, Leandro Balby Marinho, Lars Schmidt-Thieme: Tag-aware recommender systems by fusion of collaborative filtering algorithms. SAC 2008: 1995-1999

Leandro Balby Marinho, Krisztian Buza, Lars Schmidt-Thieme: Folksonomy-Based Collabulary Learning. International Semantic Web Conference 2008: 261-276

Christine Preisach, Hans Burkhardt, Lars Schmidt-Thieme, Reinhold Decker (Eds.): Data Analysis, Machine Learning and Applications - Proceedings of the 31st Annual Conference of the Gesellschaft für Klassifikation e.V., Albert-Ludwigs-Universität Freiburg, March 7-9, 2007. Studies in Classification, Data Analysis, and Knowledge Organization, Springer 2008, isbn 978-3-540-78239-1

Ernesto Diaz-Aviles, Lars Schmidt-Thieme, Cai-Nicolas Ziegler: Emergence of Spontaneous Order Through Neighborhood Formation in Peer-to-Peer Recommender Systems. CoRR abs/0812.4460 (2008)

Dominik Benz, Karen H. L. Tso, Lars Schmidt-Thieme: Supporting collaborative hierarchical classification: Bookmarks as an example. Computer Networks 51(16): 4574-4585 (2007)

Alexander Felfernig, Gerhard Friedrich, Lars Schmidt-Thieme: Guest Editors' Introduction: Recommender Systems. IEEE Intelligent Systems 22(3): 18-21 (2007)

Steffen Rendle, Lars Schmidt-Thieme: Information Integration of Partially Labeled Data. GfKl 2007: 171-179

Stefan Hauger, Karen H. L. Tso, Lars Schmidt-Thieme: Comparison of Recommender System Algorithms Focusing on the New-item and User-bias Problem. GfKl 2007: 525-532

Leandro Balby Marinho, Lars Schmidt-Thieme: Collaborative Tag Recommendations. GfKl 2007: 533-540

Manuel Stritt, Lars Schmidt-Thieme, Gerhard Poeppel: Combining multi-distributed mixture models and bayesian networks for semi-supervised learning. ICMLA 2007: 354-362

Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme, Gerd Stumme: Tag Recommendations in Folksonomies. LWA 2007: 13-20

Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme, Gerd Stumme: Tag Recommendations in Folksonomies. PKDD 2007: 506-514

Karen H. L. Tso, Lars Schmidt-Thieme: Empirical Analysis of Attribute-Aware Recommender System Algorithms Using Synthetic Data. JCP 1(4): 18-29 (2006)

Rolf Backofen, Hans-Gunther Borrmann, Werner Deck, Andreas Dedner, Luc De Raedt, Klaus Desch, Markus Diesmann, Martin Geier, Andreas Greiner, Wolfgang R. Hess, Josef Honerkamp, Stefan Jankowski, Ingo Krossing, Andreas W. Liehr, Andreas Karwath, Robert Klöfkorn, Raphaël Pesché, Tobias C. Potjans, Michael C. Röttger, Lars Schmidt-Thieme, Gerhard Schneider, Björn Voß, Bernd Wiebelt, Peter Wienemann, Volker-Henning Winterer: A Bottom-up approach to Grid-Computing at a University: the Black-Forest-Grid Initiative. Praxis der Informationsverarbeitung und Kommunikation 29(2): 81-87 (2006)

Jochen Fischer, Zeno Gantner, Steffen Rendle, Manuel Stritt, Lars Schmidt-Thieme: Ideas and Improvements for Semantic Wikis. ESWC 2006: 650-663

Manuel Stritt, Karen H. L. Tso, Lars Schmidt-Thieme: Attribute Aware Anonymous Recommender Systems. GfKl 2006: 497-504

Christine Preisach, Lars Schmidt-Thieme: Relational Ensemble Classification. ICDM 2006: 499-509

Steffen Rendle, Lars Schmidt-Thieme: Object Identification with Constraints. ICDM 2006: 1026-1031

Karen H. L. Tso, Lars Schmidt-Thieme: Evaluation of Attribute-Aware Recommender System Algorithms on Data with Varying Characteristics. PAKDD 2006: 831-840

Jens Hartmann, Nenad Stojanovic, Rudi Studer, Lars Schmidt-Thieme: Ontology-Based Query Refinement for Semantic Portals. From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments 2005: 41-50

Peter Haase, Andreas Hotho, Lars Schmidt-Thieme, York Sure: Collaborative and Usage-Driven Evolution of Personal Ontologies. ESWC 2005: 486-499

Karen H. L. Tso, Lars Schmidt-Thieme: Attribute-aware Collaborative Filtering. GfKl 2005: 614-621

Peter Fankhauser, Norbert Fuhr, Jens Hartmann, Anthony Jameson, Claus-Peter Klas, Stefan Klink, Agnes Koschmider, Sascha Kriewel, Patrick Lehti, Peter Luksch, Ernst W. Mayr, Andreas Oberweis, Paul Ortyl, Stefan Pfingstl, Patrick Reuther, Ute Rusnak, Guido Sautter, Klemens Böhm, André Schaefer, Lars Schmidt-Thieme, Eric Schwarzkopf, Nenad Stojanovic, Rudi Studer, Roland Vollmar, Bernd Walter, Alexander Weber: Fachinformationssystem Informatik (FIS-I) und Semantische Technologien für Informationsportale (SemIPort). GI Jahrestagung (2) 2005: 698-712

Lars Schmidt-Thieme: Compound Classification Models for Recommender Systems. ICDM 2005: 378-385

Peter Haase, Andreas Hotho, Lars Schmidt-Thieme, York Sure: Collaborative and Usage-driven Evolution of Personal Ontologies. LWA 2005: 151-157

Ferenc Bodon, Lars Schmidt-Thieme: The Relation of Closed Itemset Mining, Complete Pruning Strategies and Item Ordering in Apriori-Based FIM Algorithms. PKDD 2005: 437-444

Cai-Nicolas Ziegler, Georg Lausen, Lars Schmidt-Thieme: Taxonomy-driven computation of product recommendations. CIKM 2004: 406-415

Lars Schmidt-Thieme: Algorithmic Features of Eclat. FIMI 2004

Christoph Breidert, Michael Hahsler, Lars Schmidt-Thieme: Reservation Price Estimation by Adaptive Conjoint Analysis. GfKl 2004: 569-576

Martin Schader, Lars Schmidt-Thieme: Java - eine Einführung (4. Aufl.). Springer 2003, isbn 978-3-540-00663-3, pp. I-XVII, 1-634

Lars Schmidt-Thieme: Assoziationsregel-Algorithmen für Daten mit komplexer Struktur: mit Anwendungen im Web Mining. Karlsruhe Institute of Technology 2003, isbn 3-631-52213-4, pp. 1-158

Wolfgang Gaul, Lars Schmidt-Thieme: Mining Generalized Association Rules for Sequential and Path Data. ICDM 2001: 593-596