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Noam Koenigstein
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Citado por
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Año
Autoencoders
D Bank, N Koenigstein, R Giryes
Machine learning for data science handbook: data mining and knowledge …, 2023
13102023
Item2vec: neural item embedding for collaborative filtering
O Barkan, N Koenigstein
2016 IEEE 26th international workshop on machine learning for signal …, 2016
7132016
Yahoo! music recommendations: modeling music ratings with temporal dynamics and item taxonomy
N Koenigstein, G Dror, Y Koren
Proceedings of the fifth ACM conference on Recommender systems, 165-172, 2011
3952011
The Yahoo! Music Dataset and KDD-Cup’11
G Dror, N Koenigstein, Y Koren, M Weimer
KDD-Cup Workshop 2011, 2011
3712011
Speeding up the xbox recommender system using a euclidean transformation for inner-product spaces
Y Bachrach, Y Finkelstein, R Gilad-Bachrach, L Katzir, N Koenigstein, ...
Proceedings of the 8th ACM Conference on Recommender systems, 257-264, 2014
1972014
One-class collaborative filtering with random graphs
U Paquet, N Koenigstein
Proceedings of the 22nd international conference on World Wide Web, 999-1008, 2013
1162013
Efficient retrieval of recommendations in a matrix factorization framework
N Koenigstein, P Ram, Y Shavitt
Proceedings of the 21st ACM international conference on Information and …, 2012
1072012
CB2CF: a neural multiview content-to-collaborative filtering model for completely cold item recommendations
O Barkan, N Koenigstein, E Yogev, O Katz
Proceedings of the 13th ACM Conference on Recommender Systems, 228-236, 2019
1002019
Low-rank factorization of determinantal point processes
M Gartrell, U Paquet, N Koenigstein
Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017
992017
Forecasting CPI inflation components with hierarchical recurrent neural networks
O Barkan, J Benchimol, I Caspi, E Cohen, A Hammer, N Koenigstein
International Journal of Forecasting 39 (3), 1145-1162, 2023
832023
Bayesian low-rank determinantal point processes
M Gartrell, U Paquet, N Koenigstein
proceedings of the 10th ACM conference on recommender systems, 349-356, 2016
712016
Autoencoders. arxiv
D Bank, N Koenigstein, R Giryes
arXiv preprint arXiv:2003.05991, 2593-2613, 2020
702020
Machine learning for data science handbook: data mining and knowledge discovery handbook
D Bank, N Koenigstein, R Giryes
Autoencoders, 353-374, 2023
57*2023
Towards scalable and accurate item-oriented recommendations
N Koenigstein, Y Koren
Proceedings of the 7th ACM conference on Recommender systems, 419-422, 2013
552013
Beyond collaborative filtering: The list recommendation problem
O Sar Shalom, N Koenigstein, U Paquet, HP Vanchinathan
Proceedings of the 25th international conference on world wide web, 63-72, 2016
542016
Efficient modeling system for user recommendation using matrix factorization
N Nice, N Koenigstein, U Paquet, S Keren, D Sitton, D Kremer, S Roitman
US Patent 8,983,888, 2015
532015
Selecting content-based features for collaborative filtering recommenders
R Ronen, N Koenigstein, E Ziklik, N Nice
Proceedings of the 7th ACM conference on Recommender systems, 407-410, 2013
532013
Xbox movies recommendations: Variational Bayes matrix factorization with embedded feature selection
N Koenigstein, U Paquet
Proceedings of the 7th ACM Conference on Recommender Systems, 129-136, 2013
532013
Grad-sam: Explaining transformers via gradient self-attention maps
O Barkan, E Hauon, A Caciularu, O Katz, I Malkiel, O Armstrong, ...
Proceedings of the 30th ACM International Conference on Information …, 2021
492021
Scalable attentive sentence pair modeling via distilled sentence embedding
O Barkan, N Razin, I Malkiel, O Katz, A Caciularu, N Koenigstein
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3235-3242, 2020
462020
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Artículos 1–20