71 citations · 151 across the 51 of their papers we have counts for
11 papers · 1 filter
Stochastic Model Predictive Control, Iterated Function Systems, and Stability
Vyacheslav Kungurtsev, Jakub Marecek, Robert Shorten
We present the observation that the process of stochastic model predictive control can be formulated in the framework of iterated function systems. The latter has a rich ergodic th…
On the Ergodic Control of Ensembles in the Presence of Non-linear Filters
Vyacheslav Kungurtsev, Jakub Marecek, Ramen Ghosh +1
In many sharing-economy applications, as well as in conventional economy applications, one wishes to regulate the behaviour of an ensemble of agents with guarantees on both the reg…
Randomized Algorithms for Monotone Submodular Function Maximization on the Integer Lattice
Alberto Schiabel, Vyacheslav Kungurtsev, Jakub Marecek
Optimization problems with set submodular objective functions have many real-world applications. In discrete scenarios, where the same item can be selected more than once, the doma…
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks
Alexander Shevchenko, Vyacheslav Kungurtsev, Marco Mondelli
Understanding the properties of neural networks trained via stochastic gradient descent (SGD) is at the heart of the theory of deep learning. In this work, we take a mean-field vie…
Decentralized Asynchronous Non-convex Stochastic Optimization on Directed Graphs
Vyacheslav Kungurtsev, Mahdi Morafah, Tara Javidi +1
Distributed Optimization is an increasingly important subject area with the rise of multi-agent control and optimization. We consider a decentralized stochastic optimization proble…
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo
Vyacheslav Kungurtsev, Adam Cobb, Tara Javidi +1
Federated learning performed by a decentralized networks of agents is becoming increasingly important with the prevalence of embedded software on autonomous devices. Bayesian appro…
Regularized quasi-monotone method for stochastic optimization
Vyacheslav Kungurtsev, Vladimir Shikhman
We adapt the quasi-monotone method from [2] for composite convex minimization in the stochastic setting. For the proposed numerical scheme we derive the optimal convergence rate in…
On the effect of perturbations in first-order optimization methods with inertia and Hessian driven damping
Hedy Attouch, Jalal Fadili, Vyacheslav Kungurtsev
Second-order continuous-time dissipative dynamical systems with viscous and Hessian driven damping have inspired effective first-order algorithms for solving convex optimization pr…
Trilevel and Multilevel Optimization using Monotone Operator Theory
Allahkaram Shafiei, Vyacheslav Kungurtsev, Jakub Marecek
We consider rather a general class of multi-level optimization problems, where a convex objective function is to be minimized subject to constraints of optimality of nested convex…
Parametric Semidefinite Programming: Geometry of the Trajectory of Solutions
Antonio Bellon, Didier Henrion, Vyacheslav Kungurtsev +1
In many applications, solutions of convex optimization problems are updated on-line, as functions of time. In this paper, we consider parametric semidefinite programs, which are li…
Decentralized Langevin Dynamics over a Directed Graph
Alexander Kolesov, Vyacheslav Kungurtsev
The prevalence of technologies in the space of the Internet of Things and use of multi-processing computing platforms to aid in the computation required to perform learning and inf…