Guy Lebanon is affiliated with Google in the United States. Their research contributions currently include work published in 2025, primarily focusing on large-scale recommendation systems. Their recent paper is titled C2AL: Cohort-Contrastive Auxiliary Learning for Large-scale Recommendation Systems, published in arXiv (Cornell University).
Lebanon's collaborative network includes frequent co-authors involved in similar research areas. These co-authors are:
Their work is disseminated mainly through the arXiv (Cornell University) platform, reflecting engagement with pre-publication and open-access scholarly communication channels.
The scope of Lebanon's research is centered on large-scale recommendation systems, involving technical and methodological challenges relevant to machine learning and data science. This is indicated by their focus on cohort-contrastive auxiliary learning strategies for improving recommendation quality on expansive datasets.
There are no listed awards, book publications, or specified main or subfields of study associated with Lebanon in the available data. The professional profile suggests a specialization within applied machine learning and recommender systems, underpinned by collaborative development and publication of new algorithms or frameworks.
John Lafferty;Guy Lebanon
Guy Lebanon;John D. Lafferty
Guy Lebanon;John D. Lafferty
Joonseok Lee;Seungyeon Kim;Guy Lebanon;Yoram Singer
G. Lebanon
Yi Mao;Guy Lebanon
Joonseok Lee;Samy Bengio;Seungyeon Kim;Guy Lebanon
Joonseok Lee;Mingxuan Sun;Guy Lebanon
Krishnakumar Balasubramanian;Guy Lebanon
Mingxuan Sun;Fuxin Li;Joonseok Lee;Ke Zhou
Joonseok Lee;Seungyeon Kim;Guy Lebanon;Yoram Singer
Guy Lebanon;Yi Mao;Joshua Dillon
Guy Lebanon;John Lafferty
P. Kidwell;G. Lebanon;W.S. Cleveland
Guy Lebanon;John D. Lafferty
Joonseok Lee;Mingxuan Sun;Guy Lebanon
Pinar Donmez;Guy Lebanon;Krishnakumar Balasubramanian
Ashish Kamra;Elisa Bertino;Guy Lebanon
Guy Lebanon;John D. Lafferty
Yi Mao;J.V. Dillon;G. Lebanon
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