Balázs Hidasi
Balázs Hidasi
Gravity R&D
確認したメール アドレス: gravityrd.com - ホームページ
タイトル
引用先
引用先
Session-based recommendations with recurrent neural networks
B Hidasi, A Karatzoglou, L Baltrunas, D Tikk
arXiv preprint arXiv:1511.06939, 2015
11182015
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv e-prints, arXiv: 1605.02688, 2016
837*2016
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
2902017
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
2702018
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
2702016
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
1472012
General factorization framework for context-aware recommendations
B Hidasi, D Tikk
Data Mining and Knowledge Discovery, 1-30, 2015
752015
Deep learning for recommender systems
A Karatzoglou, B Hidasi
Proceedings of the eleventh ACM conference on recommender systems, 396-397, 2017
482017
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
322016
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
162012
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
152012
Speeding up ALS learning via approximate methods for context-aware recommendations
B Hidasi, D Tikk
Knowledge and Information Systems, 1-25, 2015
142015
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
142013
Factorization models for context-aware recommendations
B Hidasi
Infocommun J VI (4), 27-34, 2014
132014
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
122016
ShiftTree: An interpretable model-based approach for time series classification
B Hidasi, C Gáspár-Papanek
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
112011
Multimedia recommender systems
Y Deldjoo, M Schedl, B Hidasi, P Knees
Proceedings of the 12th ACM Conference on Recommender Systems, 537-538, 2018
102018
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
92017
Neighbor methods vs. matrix factorization—Case studies of real-life recommendations
I Pilászy, A Serény, G Dózsa, B Hidasi, A Sári, J Gub
Proceedings of the ACM RecSys 15, 2015
92015
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