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stat.ML2020
Clustering of Nonnegative Data and an Application to Matrix Completion
C. Strohmeier, D. Needell
In this paper, we propose a simple algorithm to cluster nonnegative data lying in disjoint subspaces. We analyze its performance in relation to a certain measure of correlation bet…
stat.ML2019
Bias of Homotopic Gradient Descent for the Hinge Loss
Denali Molitor, Deanna Needell, Rachel Ward
Gradient descent is a simple and widely used optimization method for machine learning. For homogeneous linear classifiers applied to separable data, gradient descent has been shown…
stat.ML2018
An iterative method for classification of binary data
Denali Molitor, Deanna Needell
In today's data driven world, storing, processing, and gleaning insights from large-scale data are major challenges. Data compression is often required in order to store large amou…