170 citations · 528 across the 46 of their papers we have counts for
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Reduced Label Complexity For Tight Regression
Alex Gittens, Malik Magdon-Ismail
Given data and labels the goal is find to minimize $\Vert{\rm X}\mathbf{w}-\mathbf{y}\V…
NoisyCUR: An algorithm for two-cost budgeted matrix completion
Dong Hu, Alex Gittens, Malik Magdon-Ismail
Matrix completion is a ubiquitous tool in machine learning and data analysis. Most work in this area has focused on the number of observations necessary to obtain an accurate low-r…
Training Deep Neural Networks with Constrained Learning Parameters
Prasanna Date, Christopher D. Carothers, John E. Mitchell +2
Today's deep learning models are primarily trained on CPUs and GPUs. Although these models tend to have low error, they consume high power and utilize large amount of memory owing…
Fast Fixed Dimension L2-Subspace Embeddings of Arbitrary Accuracy, With Application to L1 and L2 Tasks
Malik Magdon-Ismail, Alex Gittens
We give a fast oblivious L2-embedding of to satisfying $(1-\varepsilon)\|A x\|_2^2 \le \|B x\|_2^2 <= (1+\varepsilon) \|Ax\|_2^2…
PD-ML-Lite: Private Distributed Machine Learning from Lighweight Cryptography
Maksim Tsikhanovich, Malik Magdon-Ismail, Muhammad Ishaq +1
Privacy is a major issue in learning from distributed data. Recently the cryptographic literature has provided several tools for this task. However, these tools either reduce the q…
Examining the Use of Neural Networks for Feature Extraction: A Comparative Analysis using Deep Learning, Support Vector Machines, and K-Nearest Neighbor Classifiers
Stephen Notley, Malik Magdon-Ismail
Neural networks in many varieties are touted as very powerful machine learning tools because of their ability to distill large amounts of information from different forms of data,…