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1:02:58
Microsoft
Efficient Algorithms for High Dimensional Robust Learning
We study high-dimensional estimation in a setting where an adversary is allowed to arbitrarily corrupt an $varepsilon$-fraction of the samples. Such questions have a rich history spanning statistics, machine learning and theoretical computer science. Even in the most basic settings, for over fifty years the only known approaches were either ...
Apr 9, 2019
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