2 citations · 2 across the 5 of their papers we have counts for
5 papers
Understanding the Curse of Unrolling
Sheheryar Mehmood, Florian Knoll, Peter Ochs
Algorithm unrolling is ubiquitous in machine learning, particularly in hyperparameter optimization and meta-learning, where Jacobians of solution mappings are computed by different…
Automatic Differentiation of Optimization Algorithms with Time-Varying Updates
Sheheryar Mehmood, Peter Ochs
Numerous Optimization Algorithms have a time-varying update rule thanks to, for instance, a changing step size, momentum parameter or, Hessian approximation. In this paper, we appl…
Fixed-Point Automatic Differentiation of Forward--Backward Splitting Algorithms for Partly Smooth Functions
Sheheryar Mehmood, Peter Ochs
A large class of non-smooth practical optimization problems can be written as minimization of a sum of smooth and partly smooth functions. We examine such structured problems which…
Differentiating the Value Function by using Convex Duality
Sheheryar Mehmood, Peter Ochs
We consider the differentiation of the value function for parametric optimization problems. Such problems are ubiquitous in Machine Learning applications such as structured support…
Automatic Differentiation of Some First-Order Methods in Parametric Optimization
Sheheryar Mehmood, Peter Ochs
We aim at computing the derivative of the solution to a parametric optimization problem with respect to the involved parameters. For a class broader than that of strongly convex fu…