Balázs Hidasi
Balázs Hidasi
Gravity R&D
Verified email at gravityrd.com - Homepage
TitleCited byYear
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv preprint arXiv:1605.02688, 2016
6042016
Session-based recommendations with recurrent neural networks
B Hidasi, A Karatzoglou, L Baltrunas, D Tikk
arXiv preprint arXiv:1511.06939, 2015
5052015
Parallel recurrent neural network architectures for feature-rich session-based recommendations
B Hidasi, M Quadrana, A Karatzoglou, D Tikk
Proceedings of the 10th ACM conference on recommender systems, 241-248, 2016
1502016
Personalizing session-based recommendations with hierarchical recurrent neural networks
M Quadrana, A Karatzoglou, B Hidasi, P Cremonesi
Proceedings of the Eleventh ACM Conference on Recommender Systems, 130-137, 2017
1382017
Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback
B Hidasi, D Tikk
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012
1182012
Recurrent neural networks with top-k gains for session-based recommendations
B Hidasi, A Karatzoglou
Proceedings of the 27th ACM International Conference on Information and …, 2018
952018
General factorization framework for context-aware recommendations
B Hidasi, D Tikk
Data Mining and Knowledge Discovery, 1-30, 2015
512015
Deep learning for recommender systems
A Karatzoglou, B Hidasi
Proceedings of the eleventh ACM conference on recommender systems, 396-397, 2017
262017
The contextual turn: From context-aware to context-driven recommender systems
R Pagano, P Cremonesi, M Larson, B Hidasi, D Tikk, A Karatzoglou, ...
Proceedings of the 10th ACM conference on recommender systems, 249-252, 2016
252016
Initializing Matrix Factorization Methods on Implicit Feedback Databases.
B Hidasi, D Tikk
J. UCS 19 (12), 1834-1853, 2013
162013
Personalized recommendation of linear content on interactive TV platforms: beating the cold start and noisy implicit user feedback.
D Zibriczky, B Hidasi, Z Petres, D Tikk
UMAP workshops, 2012
142012
Speeding up ALS learning via approximate methods for context-aware recommendations
B Hidasi, D Tikk
Knowledge and Information Systems, 1-25, 2015
122015
Context-aware item-to-item recommendation within the factorization framework
B Hidasi, D Tikk
Proceedings of the 3rd Workshop on Context-awareness in Retrieval and …, 2013
122013
Enhancing matrix factorization through initialization for implicit feedback databases
B Hidasi, D Tikk
Proceedings of the 2nd Workshop on Context-awareness in Retrieval and …, 2012
122012
Factorization models for context-aware recommendations
B Hidasi
Infocommun J VI (4), 27-34, 2014
92014
Approximate modeling of continuous context in factorization algorithms
B Hidasi, D Tikk
Proceedings of the 4th Workshop on Context-Awareness in Retrieval and …, 2014
92014
RecSys' 16 Workshop on Deep Learning for Recommender Systems (DLRS)
A Karatzoglou, B Hidasi, D Tikk, O Sar-Shalom, H Roitman, B Shapira, ...
Proceedings of the 10th ACM Conference on Recommender Systems, 415-416, 2016
82016
Neighbor methods vs. matrix factorization-case studies of real-life recommendations
I Pilászy, A Serény, G Dózsa, B Hidasi, A Sári, J Gub
LSRS Workshop at ACM RecSys, 2015
82015
Dlrs 2017: Second workshop on deep learning for recommender systems
B Hidasi, A Karatzoglou, O Sar-Shalom, S Dieleman, B Shapira, D Tikk
Proceedings of the Eleventh ACM Conference on Recommender Systems, 370-371, 2017
72017
Context-aware recommendations from implicit data via scalable tensor factorization
B Hidasi, D Tikk
arXiv preprint arXiv:1309.7611, 2013
72013
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Articles 1–20