Julian Katz-Samuels

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State legislatures introduce at least 45,000 bills each year. However, we lack a clear understanding of who is actually writing those bills. As legislators often lack the time and staff to draft each bill, they frequently copy text written by other states or interest groups. However, existing approaches to detect text reuse are slow, biased, and incomplete.(More)
We consider the task of collaborative preference completion: given a pool of items, a pool of users and a partially observed item-user rating matrix, the goal is to recover the personalized ranking of each user over all of the items. Our approach is nonparametric: we assume that each item i and each user u have unobserved features xi and yu, and that the(More)
The first term is the estimation error and measures the performance of the discrimination rule with respect to the best hypothesis in H. In previous lectures, we studied performance guarantees for this quantity when ĥn is ERM. Now, we also consider the approximation error, which captures how well a class of hypotheses {Hk} approximates the Bayes decision(More)
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