37 citations · 44 across the 8 of their papers we have counts for
8 papers
Truthful Online Scheduling of Cloud Workloads under Uncertainty
Moshe Babaioff, Ronny Lempel, Brendan Lucier +3
Cloud computing customers often submit repeating jobs and computation pipelines on \emph{approximately} regular schedules, with arrival and running times that exhibit variance. Thi…
Productization Challenges of Contextual Multi-Armed Bandits
David Abensur, Ivan Balashov, Shaked Bar +5
Contextual Multi-Armed Bandits is a well-known and accepted online optimization algorithm, that is used in many Web experiences to tailor content or presentation to users' traffic.…
Search-Based Serving Architecture of Embeddings-Based Recommendations
Sonya Liberman, Shaked Bar, Raphael Vannerom +2
Over the past 10 years, many recommendation techniques have been based on embedding users and items in latent vector spaces, where the inner product of a (user,item) pair of vector…
Budget-Constrained Item Cold-Start Handling in Collaborative Filtering Recommenders via Optimal Design
Oren Anava, Shahar Golan, Nadav Golbandi +4
It is well known that collaborative filtering (CF) based recommender systems provide better modeling of users and items associated with considerable rating history. The lack of his…
Distributed Exploration in Multi-Armed Bandits
Eshcar Hillel, Zohar Karnin, Tomer Koren +2
We study exploration in Multi-Armed Bandits in a setting where players collaborate in order to identify an -optimal arm. Our motivation comes from recent employment of bandi…
OFF-Set: One-pass Factorization of Feature Sets for Online Recommendation in Persistent Cold Start Settings
Michal Aharon, Natalie Aizenberg, Edward Bortnikov +6
One of the most challenging recommendation tasks is recommending to a new, previously unseen user. This is known as the 'user cold start' problem. Assuming certain features or attr…