1 citations · 3 across the 11 of their papers we have counts for
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Reciprocal-Manifold Annealed KKT Flows for Constrained Optimization: Application to the Nonconvex AC Optimal Power Flow
M Parimi, Aditi Ramteke, Rachit Mehra +2
Safety-critical optimization applications, such as real-time power system operation, maintain feasibility at every intermediate step, not merely at convergence. Existing approaches…
Almost Sure Convergence and Non-asymptotic Concentration Bounds for Stochastic Mirror Descent Algorithm
Anik Kumar Paul, Arun D Mahindrakar, Rachel K Kalaimani
This letter investigates the convergence and concentration properties of the Stochastic Mirror Descent (SMD) algorithm utilizing biased stochastic subgradients. We establish the al…
Convergence Analysis of Stochastic Saddle Point Mirror Descent Algorithm -- A Projected Dynamical View Point
Anik Kumar Paul, Arun D Mahindrakar, Rachel K Kalaimani
Saddle point problems, ubiquitous in optimization, extend beyond game theory to diverse domains like power networks and reinforcement learning. This paper presents novel approaches…
Dynamical System Approach for Time-Varying Constrained Convex Optimization Problems
Rejitha Raveendran, Arun D. Mahindrakar, Umesh Vaidya
Optimization problems emerging in most of the real-world applications are dynamic, where either the objective function or the constraints change continuously over time. This paper…
Robust Analysis of Almost Sure Convergence of Zeroth-Order Mirror Descent Algorithm
Anik Kumar Paul, Arun D Mahindrakar, Rachel K Kalaimani
This letter presents an almost sure convergence of the zeroth-order mirror descent algorithm. The algorithm admits non-smooth convex functions and a biased oracle which only provid…
Complex Laplacian based Distributed Control for Multi-Agent Network
Aniket Deshpande, Pushpak Jagtap, Prashant Bansode +2
The work done in this paper, proposes a complex Laplacian-based distributed control scheme for convergence in the multi-agent network. The proposed scheme has been designated as ca…