3.4k citations · 5k across the 80 of their papers we have counts for
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Spectral Algorithm for Low-rank Multitask Regression
Yotam Gigi, Ami Wiesel, Sella Nevo +3
Multitask learning, i.e. taking advantage of the relatedness of individual tasks in order to improve performance on all of them, is a core challenge in the field of machine learnin…
Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies
Tom Zahavy, Avinatan Hasidim, Haim Kaplan +1
We consider a settings of hierarchical reinforcement learning, in which the reward is a sum of components. For each component we are given a policy that maximizes it and our goal i…
Learning to Screen
Alon Cohen, Avinatan Hassidim, Haim Kaplan +2
Imagine a large firm with multiple departments that plans a large recruitment. Candidates arrive one-by-one, and for each candidate the firm decides, based on her data (CV, skills,…
ML for Flood Forecasting at Scale
Sella Nevo, Vova Anisimov, Gal Elidan +11
Effective riverine flood forecasting at scale is hindered by a multitude of factors, most notably the need to rely on human calibration in current methodology, the limited amount o…
Towards Global Remote Discharge Estimation: Using the Few to Estimate The Many
Yotam Gigi, Gal Elidan, Avinatan Hassidim +5
Learning hydrologic models for accurate riverine flood prediction at scale is a challenge of great importance. One of the key difficulties is the need to rely on in-situ river disc…