Author

Peyman Mohajerin Esfahani

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Preprint Oct 2026

Learning in Inverse Games: Tractable Training with Probabilistic Guarantees

Inverse game theory seeks to learn agents'unknown objectives from observed equilibrium behavior. Existing residual-based approaches can lead to non-convex problems and need not ensure strong monotonicity of the learned game, limiting reliable equilibrium prediction. We develop a tractable convex framework for learning...

Arghya Mallick, R. R. Baghbadorani, Peyman Mohajerin Esfahani et al. · 0 citations

Preprint Sep 2026

Benign Geometry and Distributional Robustness of $\mathcal{H}_2$ Synthesis

In this paper, we study standard and distributionally robust $\mathcal{H}_2$ synthesis problem of a stabilizing state-feedback controller for discrete-time linear time-invariant systems. Without requiring a nonsingular disturbance controllability Gramian or a positive-definite control penalty, we establish that station...

A. S. Kolarijani, Peyman Mohajerin Esfahani, Tamás Keviczky et al. · 0 citations

#machine learning Preprint Sep 2026

Limiting-Kernel Q($\lambda$): Bridging Short and Long Horizons

In value-based reinforcement learning, improving the accuracy of policy evaluation has been shown to improve downstream policy optimization performance. The widely adopted family of approximations relying on $n$-step truncation yields computationally efficient value estimators but is inherently limited to a short evalu...

Tolga Ok, A. S. Kolarijani, Peyman Mohajerin Esfahani et al. · 0 citations