
Correcting the bias in least squares regression with volumerescaled sampling
Consider linear regression where the examples are generated by an unknow...
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Minimax experimental design: Bridging the gap between statistical and worstcase approaches to least squares regression
In experimental design, we are given a large collection of vectors, each...
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Tail bounds for volume sampled linear regression
The n × d design matrix in a linear regression problem is given, but the...
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Reverse iterative volume sampling for linear regression
We study the following basic machine learning task: Given a fixed set of...
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Fast determinantal point processes via distortionfree intermediate sampling
Given a fixed n× d matrix X, where n≫ d, we study the complexity of samp...
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Michal Derezinski
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