Theory Seminar: Efficient Optimization in Machine Learning

דובר:
אלעד חזן (טכניון)
תאריך:
יום רביעי, 30.11.2011, 12:30
מקום:
טאוב 201

Linear classification is a fundamental problem of machine learning, in which positive and negative examples of a concept are represented in Euclidean space by their feature vectors, and we seek to find a hyperplane separating the two classes of vectors.

In this talk we'll describe recent advances in efficient algorithms for linear classification and related machine learning problems. In particular we'll describe the first sublinear-time (information-optimal) algorithms for linear classification and discuss when can optimization time meets the information limit.

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