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Iterative Sketching for Secure Coded Regression
Linear regression is a fundamental and primitive problem in supervised machine learning, with applications ranging from epidemiology to finance.
Gradient Coding through Iterative Block Leverage Score Sampling
This is then used to derive an approximate coded computing approach for first-order methods; known as gradient coding, to accelerate linear regression in the presence of failures in distributed computational networks, \textit{i. e.} stragglers.
Dimensionality Reduction for $k$-means Clustering
We present a study on how to effectively reduce the dimensions of the $k$-means clustering problem, so that provably accurate approximations are obtained.
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