332 citations
- Tel Aviv UniversityIL25 papers
- Google (United States)US19 papers
- Technion – Israel Institute of TechnologyIL13 papers
- Hebrew University of JerusalemIL7 papers
- Bar-Ilan UniversityIL3 papers
- Weizmann Institute of ScienceIL3 papers
- Ben-Gurion University of the NegevIL2 papers
- Cornell UniversityUS2 papers
- Massachusetts Institute of TechnologyUS2 papers
- Microsoft (United States)US2 papers
- University of PennsylvaniaUS2 papers
- Aix-Marseille UniversitéFR1 paper
19 papers · 1 filter
Batch Ensemble for Variance Dependent Regret in Stochastic Bandits
Asaf Cassel, Orin Levy, Yishay Mansour
Efficiently trading off exploration and exploitation is one of the key challenges in online Reinforcement Learning (RL). Most works achieve this by carefully estimating the model u…
Improving Training Stability for Multitask Ranking Models in Recommender Systems
Jiaxi Tang, Yoel Drori, Daryl Chang +6
Recommender systems play an important role in many content platforms. While most recommendation research is dedicated to designing better models to improve user experience, we foun…
Rate-Optimal Online Convex Optimization in Adaptive Linear Control
Asaf Cassel, Alon Cohen, Tomer Koren
We consider the problem of controlling an unknown linear dynamical system under adversarially changing convex costs and full feedback of both the state and cost function. We presen…
Differentially-Private Clustering of Easy Instances
Edith Cohen, Haim Kaplan, Yishay Mansour +2
Clustering is a fundamental problem in data analysis. In differentially private clustering, the goal is to identify cluster centers without disclosing information on individual…
Nonstochastic Bandits with Composite Anonymous Feedback
Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni +2
We investigate a nonstochastic bandit setting in which the loss of an action is not immediately charged to the player, but rather spread over the subsequent rounds in an adversaria…
Flood forecasting with machine learning models in an operational framework
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal +28
The operational flood forecasting system by Google was developed to provide accurate real-time flood warnings to agencies and the public, with a focus on riverine floods in large,…