13 citations · 20 across the 42 of their papers we have counts for
65 papers
Limiting-Kernel Q(): Bridging Short and Long Horizons
Tolga Ok, Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani +1
In value-based reinforcement learning, improving the accuracy of policy evaluation has been shown to improve downstream policy optimization performance. The widely adopted family o…
Benign Geometry and Distributional Robustness of Synthesis
Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani, Tamás Keviczky +1
In this paper, we study standard and distributionally robust synthesis problem of a stabilizing state-feedback controller for discrete-time linear time-invariant sy…
Adaptive Incentive Design in Dynamic Principal-Agent Problem via Kernelized Bandits
Arghya Mallick, Anuj S. Vora, Sergio Grammatico +1
We consider the dynamic principal-agent problem under asymmetric information, wherein a principal sequentially designs contracts to incentivize an agent with unknown preferences an…
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…
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…
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…