collaborators

24 papers

math.OC2026

Discrete-Time Adaptive Control in High Dimensions: Near Dimension-Free Performance via Mirror Descent

Mohammad Boveiri, Peyman Mohajerin Esfahani

Motivated by the use of modern high-capacity models in real-time control problems, this paper studies the adaptive control of high-dimensional discrete-time nonlinear systems with…

cs.LG2026

Nonlinear Bayesian Estimator for Parameter Learning: A Fixed-Point Characterization

Sasan Vakili, Daniël Woonings, Pradyumna Paruchuri +1

This paper presents a nonlinear parameter estimator for Wiener-type state-space models obtained as a fixed-point architecture that couples two affine minimum mean-squared error (MM…

stat.ML2026

Tight Generalization Bounds for Noiseless Inverse Optimization

Pouria Fatemi, Hoomaan Maskan, Suvrit Sra +1

Inverse optimization (IO) seeks to infer the parameters of a decision-maker's objective from observed context--action data. We study noiseless IO, where demonstrations are generate…

math.OC2026

Locally Linear Convergence for Nonsmooth Convex Optimization via Coupled Smoothing and Momentum

Reza Rahimi Baghbadorani, Sergio Grammatico, Peyman Mohajerin Esfahani

We propose an adaptive accelerated smoothing technique for a nonsmooth convex optimization problem where the smoothing update rule is coupled with the momentum parameter. We also e…

math.OC2026

A Saddle Point Algorithm for Robust Data-Driven Factor Model Problems

Shabnam Khodakaramzadeh, Soroosh Shafiee, Gabriel de Albuquerque Gleizer +1

We study the factor model problem, which aims to uncover low-dimensional structures in high-dimensional datasets. Adopting a robust data-driven approach, we formulate the problem a…

math.OC2026

A Hybrid Algorithm for Monotone Variational Inequalities

Reza Rahimi Baghbadorani, Peyman Mohajerin Esfahani, Sergio Grammatico

Inspired by the adaptive Golden Ratio Algorithm (aGRAAL), we propose two new methods for solving monotone variational inequalities. We show that by selecting the momentum parameter…