The fused Lasso penalty enforces sparsity in both the coefficients and their successive differences, which is desirable for applications with features ordered in some meaningful w...
Recommender systems are an emerging technology that helps consumers to find interesting products. A recommender system makes personalized product suggestions by extracting knowle...
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
With increasing deployment of systems involving multiple coordinating agents, there is a growing need for diagnosing coordination failures in such systems. Previous work presented...
Meir Kalech, Gal A. Kaminka, Amnon Meisels, Yehuda...
In our prior work, we introduced a generalization of the multiple-instance learning (MIL) model in which a bag's label is not based on a single instance's proximity to a...