146 citations · 222 across the 3 of their papers we have counts for
3 papers
cs.LG2015★ 146 cited
Learn on Source, Refine on Target:A Model Transfer Learning Framework with Random Forests
Noam Segev, Maayan Harel, Shie Mannor +2
We propose novel model transfer-learning methods that refine a decision forest model M learned within a "source" domain using a training set sampled from a "target" domain, assumed…
cs.LG2012★ 2 cited
The Perturbed Variation
Maayan Harel, Shie Mannor
We introduce a new discrepancy score between two distributions that gives an indication on their similarity. While much research has been done to determine if two samples come from…
cs.LG2010★ 74 cited
Learning from Multiple Outlooks
Maayan Harel, Shie Mannor
We propose a novel problem formulation of learning a single task when the data are provided in different feature spaces. Each such space is called an outlook, and is assumed to con…