67 citations · 350 across the 31 of their papers we have counts for
4 papers · 1 filter
Iterative thresholding for non-linear learning in the strong -contamination model
Arvind Rathnashyam, Alex Gittens
We derive approximation bounds for learning single neuron models using thresholded gradient descent when both the labels and the covariates are possibly corrupted adversarially. We…
Extending Model-x Framework to Missing Data
Deniz Koyuncu, Alex Gittens, Bülent Yener
One limitation of the most statistical/machine learning-based variable selection approaches is their inability to control the false selections. A recently introduced framework, mod…
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
Shusen Wang, Alex Gittens, Michael W. Mahoney
We address the statistical and optimization impacts of the classical sketch and Hessian sketch used to approximately solve the Matrix Ridge Regression (MRR) problem. Prior research…
Compact Random Feature Maps
Raffay Hamid, Ying Xiao, Alex Gittens +1
Kernel approximation using randomized feature maps has recently gained a lot of interest. In this work, we identify that previous approaches for polynomial kernel approximation cre…