8 citations · 8 across the 3 of their papers we have counts for
9 papers
A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond
Philip Intallura, Georgios Korpas, Sudeepto Chakraborty +4
Monte Carlo sampling is a powerful toolbox of algorithmic techniques widely used for a number of applications wherein some noisy quantity, or summary statistic thereof, is sought t…
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…
Numerical Algorithms for Partially Segregated Elliptic Systems
Farid Bozorgnia, Avetik Arakelyan, Vyacheslav Kungurtsev +1
We develop numerical methods for elliptic systems governed by partial segregation constraints, in which three nonnegative components are required to have a vanishing pointwise prod…
Tame Riemannian Stochastic Approximation
Johannes Aspman, Vyacheslav Kungurtsev, Reza Roohi Seraji
We study the properties of stochastic approximation applied to a tame nondifferentiable function subject to constraints defined by a Riemannian manifold. The objective landscape of…
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…