activity
20202026
collaborators

7 papers

math.OC2026

Transform Method for Stochastic Processing and Matching Networks

Sushil Mahavir Varma, Prakirt Jhunjhunwala, Daniela Hurtado-Lange +1

Modern service systems, ranging from cloud data centers and ride-hailing platforms to healthcare facilities, operate at massive scales where it is important to handle congestion. Q…

stat.ML2026

Phase Transition in Convex Relaxations for Graph Alignment

Laurent Massoulié, Sushil Mahavir Varma, Louis Vassaux +1

We study the graph alignment problem for correlated Gaussian Orthogonal Ensemble (GOE) matrices, where the goal is to recover a hidden vertex permutation given two correlated symme…

cs.LG2025

Near-Optimal Regret-Queue Length Tradeoff in Online Learning for Two-Sided Markets

Zixian Yang, Sushil Mahavir Varma, Lei Ying

We study a two-sided market, wherein, price-sensitive heterogeneous customers and servers arrive and join their respective queues. A compatible customer-server pair can then be mat…

math.PR2025

Finite-Time Behavior of Erlang-C Model: Mixing Time, Mean Queue Length and Tail Bounds

Hoang Huy Nguyen, Sushil Mahavir Varma, Siva Theja Maguluri

Service systems like data centers and ride-hailing are popularly modeled as queueing systems in the literature. Such systems are primarily studied in the steady state due to their…

stat.ML2025

Graph Alignment via Birkhoff Relaxation

Sushil Mahavir Varma, Irène Waldspurger, Laurent Massoulié

We consider the graph alignment problem, wherein the objective is to find a vertex correspondence between two graphs that maximizes the edge overlap. The graph alignment problem is…

cs.LG2021

On the Linear convergence of Natural Policy Gradient Algorithm

Sajad Khodadadian, Prakirt Raj Jhunjhunwala, Sushil Mahavir Varma +1

Markov Decision Processes are classically solved using Value Iteration and Policy Iteration algorithms. Recent interest in Reinforcement Learning has motivated the study of methods…