Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Noam Koenigstein"'
Publikováno v:
IEEE Access, Vol 11, Pp 34746-34763 (2023)
Collaborative filtering methods for recommender systems tend to represent users as a single static latent vector. However, user behavior and interests may dynamically change in the context of the recommended item being presented to the user. For exam
Externí odkaz:
https://doaj.org/article/15728250afc6455b8e446e35504906bf
Autor:
Abiola Owoyemi, Ron Porat, Amnon Lichter, Adi Doron-Faigenboim, Omri Jovani, Noam Koenigstein, Yael Salzer
Publikováno v:
Horticulturae, Vol 8, Iss 7, p 570 (2022)
We conducted a large-scale, high-throughput phenotyping analysis of the effects of various preharvest and postharvest features on the quality of ‘Valencia’ oranges in order to develop shelf-life prediction models. Altogether, we evaluated 10,800
Externí odkaz:
https://doaj.org/article/4ac7fa2aa3ce46f595fb8dfeb7da7649
Autor:
Abiola Owoyemi, Ron Porat, Amnon Lichter, Adi Doron-Faigenboim, Omri Jovani, Noam Koenigstein, Yael Salzer
Publikováno v:
Foods, Vol 11, Iss 13, p 1840 (2022)
We conducted a large-scale, high-throughput phenotyping analysis of the effects of various pre-harvest and postharvest features on the quality of ‘Rustenburg’ navel oranges, in order to develop shelf-life prediction models to enable the use of th
Externí odkaz:
https://doaj.org/article/688974e8e6144615833107d1fba1178c
Autor:
Noam Koenigstein, Jonathan Weill, Ori Katz, Itzik Malkiel, Idan Rejwan, Avi Caciularu, Oren Barkan
Publikováno v:
CIKM
We present Variational Bayesian Network (VBN) - a novel Bayesian entity representation learning model that utilizes hierarchical and relational side information and is particularly useful for modeling entities in the ``long-tail'', where the data is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6ad07e3e83174dd148cfa6f08f039bf
Publikováno v:
Sixteenth ACM Conference on Recommender Systems.
We present MetricBERT, a BERT-based model that learns to embed text under a well-defined similarity metric while simultaneously adhering to the ``traditional'' masked-language task. We focus on downstream tasks of learning similarities for recommenda
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a045c69568b3c9c45d7e6ce955151bd
http://arxiv.org/abs/2208.06610
http://arxiv.org/abs/2208.06610
Recently, there has been growing interest in the ability of Transformer-based models to produce meaningful embeddings of text with several applications, such as text similarity. Despite significant progress in the field, the explanations for similari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d79e8a18d044aa5685a11e9ffd86ba4b
http://arxiv.org/abs/2208.06612
http://arxiv.org/abs/2208.06612
Autor:
Salzer, Abiola Owoyemi, Ron Porat, Amnon Lichter, Adi Doron-Faigenboim, Omri Jovani, Noam Koenigstein, Yael
Publikováno v:
Horticulturae; Volume 8; Issue 7; Pages: 570
We conducted a large-scale, high-throughput phenotyping analysis of the effects of various preharvest and postharvest features on the quality of ‘Valencia’ oranges in order to develop shelf-life prediction models. Altogether, we evaluated 10,800
Publikováno v:
International Journal of Forecasting.
We present a hierarchical architecture based on Recurrent Neural Networks (RNNs) for predicting disaggregated inflation components of the Consumer Price Index (CPI). While the majority of existing research is focused mainly on predicting the inflatio