6 citations · 21 across the 11 of their papers we have counts for
4 papers · 1 filter
Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis
Daniel P. Robinson, Rene Vidal, Chong You
Given an overcomplete dictionary and a signal for some sparse vector whose nonzero entries correspond to linearly independent columns of , classical sparse…
Trust-Region Newton-CG with Strong Second-Order Complexity Guarantees for Nonconvex Optimization
Frank E. Curtis, Daniel P. Robinson, Clément Royer +1
Worst-case complexity guarantees for nonconvex optimization algorithms have been a topic of growing interest. Multiple frameworks that achieve the best known complexity bounds amon…
What is the Largest Sparsity Pattern that Can Be Recovered by 1-Norm Minimization?
Mustafa D. Kaba, Mengnan Zhao, Rene Vidal +2
Much of the existing literature in sparse recovery is concerned with the following question: given a sparsity pattern and a corresponding regularizer, derive conditions on the dict…
Conformal Symplectic and Relativistic Optimization
Guilherme França, Jeremias Sulam, Daniel P. Robinson +1
Arguably, the two most popular accelerated or momentum-based optimization methods in machine learning are Nesterov's accelerated gradient and Polyaks's heavy ball, both correspondi…