141 citations · 310 across the 29 of their papers we have counts for
8 papers · 1 filter
A New Class of Composite Objective Multi-step Estimating-sequence Techniques (COMET)
Endrit Dosti, Sergiy A. Vorobyov, Themistoklis Charalambous
We devise a new accelerated gradient-based estimating sequence technique for solving large-scale optimization problems with composite structure. More specifically, we introduce a n…
Internal and String Stability of an Observer-based Controller for Vehicle Platooning under the MPF Topology
Wei Jiang, Elham Abolfazli, Themistoklis Charalambous
In this paper, we study the internal stability and string stability of a vehicle platoon under the constant time headway spacing (CTHS) policy and the multiple-predecessor-followin…
A convex relaxation approach for the optimized pulse pattern problem
Lukas Wachter, Orcun Karaca, Georgios Darivianakis +1
Optimized Pulse Patterns (OPPs) are gaining increasing popularity in the power electronics community over the well-studied pulse width modulation due to their inherent ability to p…
Embedding a Heavy-Ball type of Momentum into the Estimating Sequences
Endrit Dosti, Sergiy A. Vorobyov, Themistoklis Charalambous
We present a new accelerated gradient-based method for solving smooth unconstrained optimization problems. The goal is to embed a heavy-ball type of momentum into the Fast Gradient…
Infinite Horizon Average Cost Dynamic Programming Subject to Total Variation Distance Ambiguity
Ioannis Tzortzis, Charalambos D. Charalambous, Themistoklis Charalambous
We analyze the infinite horizon minimax average cost Markov Control Model (MCM), for a class of controlled process conditional distributions, which belong to a ball, with respect t…
Approximation of Markov Processes by Lower Dimensional Processes via Total Variation Metrics
Ioannis Tzortzis, Charalambos D. Charalambous, Themistoklis Charalambous +2
The aim of this paper is to approximate a finite-state Markov process by another process with fewer states, called herein the approximating process. The approximation problem is fo…