8 citations · 8 across the 3 of their papers we have counts for
7 papers · 1 filter
Optimal Control in Hilbert Complex Spaces with Finite Element Exterior Calculus
Farid Bozorgnia, Michael Holst, Anshu Kumar +3
We develop a framework for PDE-constrained optimal control on Hilbert complexes and its structure-preserving discretization by finite element exterior calculus (FEEC), with emphasi…
Direct-search methods for decentralized blackbox optimization
El Houcine Bergou, Youssef Diouane, Vyacheslav Kungurtsev +1
Derivative-free optimization algorithms are particularly useful for tackling blackbox optimization problems where the objective function arises from complex and expensive procedure…
Stochastic Approximation for Expectation Objective and Expectation Inequality-Constrained Nonconvex Optimization
Francisco Facchinei, Vyacheslav Kungurtsev
Stochastic Approximation has been a prominent set of tools for solving problems with noise and uncertainty. Increasingly, it becomes important to solve optimization problems wherei…
Time-Varying Multi-Objective Optimization: Tradeoff Regret Bounds
Allahkaram Shafiei, Jakub Marecek
Multi-objective optimization studies the process of seeking multiple competing desiderata in some operation. Solution techniques highlight marginal tradeoffs associated with weighi…
A Sequential Quadratic Programming Method for Optimization with Stochastic Objective Functions, Deterministic Inequality Constraints and Robust Subproblems
Songqiang Qiu, Vyacheslav Kungurtsev
In this paper, a robust sequential quadratic programming method for constrained optimization is generalized to problem with an {expectation} objective function {and} deterministic…
Stochastic Langevin Differential Inclusions with Applications to Machine Learning
Fabio V. Difonzo, Vyacheslav Kungurtsev, Jakub Marecek
Stochastic differential equations of Langevin-diffusion form have received significant attention, thanks to their foundational role in both Bayesian sampling algorithms and optimiz…