Christoph Freudenthaler
Christoph Freudenthaler
Student of Economics, Johannes Kepler University, Linz
No verified email
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Cited by
Cited by
Year
BPR: Bayesian personalized ranking from implicit feedback
S Rendle, C Freudenthaler, Z Gantner, L Schmidt-Thieme
arXiv preprint arXiv:1205.2618, 2012
36822012
Factorizing personalized markov chains for next-basket recommendation
S Rendle, C Freudenthaler, L Schmidt-Thieme
Proceedings of the 19th international conference on World wide web, 811-820, 2010
10852010
Fast context-aware recommendations with factorization machines
S Rendle, Z Gantner, C Freudenthaler, L Schmidt-Thieme
Proceedings of the 34th international ACM SIGIR conference on Research and …, 2011
5262011
MyMediaLite: A free recommender system library
Z Gantner, S Rendle, C Freudenthaler, L Schmidt-Thieme
Proceedings of the fifth ACM conference on Recommender systems, 305-308, 2011
4572011
Learning attribute-to-feature mappings for cold-start recommendations
Z Gantner, L Drumond, C Freudenthaler, S Rendle, L Schmidt-Thieme
2010 IEEE International Conference on Data Mining, 176-185, 2010
3162010
Improving pairwise learning for item recommendation from implicit feedback
S Rendle, C Freudenthaler
Proceedings of the 7th ACM international conference on Web search and data …, 2014
2712014
Multi-relational matrix factorization using bayesian personalized ranking for social network data
A Krohn-Grimberghe, L Drumond, C Freudenthaler, L Schmidt-Thieme
Proceedings of the fifth ACM international conference on Web search and data …, 2012
1792012
Personalized ranking for non-uniformly sampled items
Z Gantner, L Drumond, C Freudenthaler, L Schmidt-Thieme
Proceedings of KDD Cup 2011, 231-247, 2012
752012
Non-myopic active learning for recommender systems based on matrix factorization
R Karimi, C Freudenthaler, A Nanopoulos, L Schmidt-Thieme
2011 IEEE International Conference on Information Reuse & Integration, 299-303, 2011
362011
Bayesian factorization machines
C Freudenthaler, L Schmidt-Thieme, S Rendle
352011
Exploiting the characteristics of matrix factorization for active learning in recommender systems
R Karimi, C Freudenthaler, A Nanopoulos, L Schmidt-Thieme
Proceedings of the sixth ACM conference on Recommender systems, 317-320, 2012
292012
Towards optimal active learning for matrix factorization in recommender systems
R Karimi, C Freudenthaler, A Nanopoulos, L Schmidt-Thieme
2011 IEEE 23rd International Conference on Tools with Artificial …, 2011
252011
Active learning for aspect model in recommender systems
R Karimi, C Freudenthaler, A Nanopoulos, L Schmidt-Thieme
2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM …, 2011
252011
Gender differences in risk-taking: Evidence from professional basketball
R Böheim, C Freudenthaler, M Lackner
IZA Discussion Paper, 2016
132016
Comparing Prediction Models for Active Learning in Recommender Systems.
R Karimi, C Freudenthaler, A Nanopoulos, L Schmidt-Thieme
LWA, 171-180, 2015
102015
Factorization Machines Factorized Polynomial Regression Models
C Freudenthaler, L Schmidt-thieme, S Rendle
92009
Keyword-based tv program recommendation
C Wartena, W Slakhorst, M Wibbels, Z Gantner, C Freudenthaler, ...
ITWP@ IJCAI, 2011
52011
MyMedia: producing an extensible framework for recommendation
P Marrow, R Hanbidge, S Rendle, C Wartena, C Freudenthaler
Networked Electronic Media Summit, 2009
52009
Optimal ranking for video recommendation
Z Gantner, C Freudenthaler, S Rendle, L Schmidt-Thieme
International Conference on User Centric Media, 255-258, 2009
32009
Collective matrix factorization of predictors, neighborhood and targets for semi-supervised classification
LR Drumond, L Schmidt-Thieme, C Freudenthaler, A Krohn-Grimberghe
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 286-297, 2014
22014
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Articles 1–20