6 citations · 11 across the 5 of their papers we have counts for
3 papers · 1 filter
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update
Michał Dereziński, Jonathan Lacotte, Mert Pilanci +1
In second-order optimization, a potential bottleneck can be computing the Hessian matrix of the optimized function at every iteration. Randomized sketching has emerged as a powerfu…
Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality
Jonathan Lacotte, Yifei Wang, Mert Pilanci
We propose a randomized algorithm with quadratic convergence rate for convex optimization problems with a self-concordant, composite, strongly convex objective function. Our method…
Fast Convex Quadratic Optimization Solvers with Adaptive Sketching-based Preconditioners
Jonathan Lacotte, Mert Pilanci
We consider least-squares problems with quadratic regularization and propose novel sketching-based iterative methods with an adaptive sketch size. The sketch size can be as small a…