732 citations · 1.7k across the 44 of their papers we have counts for
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Efficient Greedy Coordinate Descent for Composite Problems
Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich +1
Coordinate descent with random coordinate selection is the current state of the art for many large scale optimization problems. However, greedy selection of the steepest coordinate…
Global linear convergence of Newton's method without strong-convexity or Lipschitz gradients
Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi
We show that Newton's method converges globally at a linear rate for objective functions whose Hessians are stable. This class of problems includes many functions which are not str…
On Matching Pursuit and Coordinate Descent
Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy +4
Two popular examples of first-order optimization methods over linear spaces are coordinate descent and matching pursuit algorithms, with their randomized variants. While the former…