71 citations · 151 across the 51 of their papers we have counts for
8 papers · 1 filter
Quantum Solutions to the Privacy vs. Utility Tradeoff
Sagnik Chatterjee, Vyacheslav Kungurtsev
In this work, we propose a novel architecture (and several variants thereof) based on quantum cryptographic primitives with provable privacy and security guarantees regarding membe…
Inexact Direct-Search Methods for Bilevel Optimization Problems
Youssef Diouane, Vyacheslav Kungurtsev, Francesco Rinaldi +1
In this work, we introduce new direct search schemes for the solution of bilevel optimization (BO) problems. Our methods rely on a fixed accuracy black box oracle for the lower-lev…
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…
Hybrid Methods in Polynomial Optimisation
Johannes Aspman, Gilles Bareilles, Vyacheslav Kungurtsev +2
The Moment/Sum-of-squares hierarchy provides a way to compute the global minimizers of polynomial optimization problems (POP), at the cost of solving a sequence of increasingly lar…
A Stochastic-Gradient-based Interior-Point Algorithm for Solving Smooth Bound-Constrained Optimization Problems
Frank E. Curtis, Vyacheslav Kungurtsev, Daniel P. Robinson +1
A stochastic-gradient-based interior-point algorithm for minimizing a continuously differentiable objective function (that may be nonconvex) subject to bound constraints is present…
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…
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…
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…