27 citations · 149 across the 34 of their papers we have counts for
4 papers · 1 filter
Combining Structured and Unstructured Randomness in Large Scale PCA
Nikos Karampatziakis, Paul Mineiro
Principal Component Analysis (PCA) is a ubiquitous tool with many applications in machine learning including feature construction, subspace embedding, and outlier detection. In thi…
Discriminative Features via Generalized Eigenvectors
Nikos Karampatziakis, Paul Mineiro
Representing examples in a way that is compatible with the underlying classifier can greatly enhance the performance of a learning system. In this paper we investigate scalable tec…
Loss-Proportional Subsampling for Subsequent ERM
Paul Mineiro, Nikos Karampatziakis
We propose a sampling scheme suitable for reducing a data set prior to selecting a hypothesis with minimum empirical risk. The sampling only considers a subset of the ultimate (unk…
Normalized Online Learning
Stephane Ross, Paul Mineiro, John Langford
We introduce online learning algorithms which are independent of feature scales, proving regret bounds dependent on the ratio of scales existent in the data rather than the absolut…