Fairness in Supervised Learning: An Information Theoretic Approach. - AmirEmad Ghassami; Sajad Khodadadian; Negar Kiyavash (ISIT, 2018)

On the Linear Convergence of Natural Policy Gradient Algorithm. - Sajad Khodadadian; Prakirt Raj Jhunjhunwala; Sushil Mahavir Varma; Siva Theja Maguluri (CDC, 2021)

Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm. - Sajad Khodadadian; Zaiwei Chen; Siva Theja Maguluri (ICML, 2021)

Impact of Data Processing on Fairness in Supervised Learning. - Sajad Khodadadian; AmirEmad Ghassami; Negar Kiyavash (ISIT, 2021)

Information Theoretic Measures for Fairness-aware Feature Selection. - Sajad Khodadadian; Mohamed S. Nafea; AmirEmad Ghassami; Negar Kiyavash (CoRR, 2021)

Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling. - Sajad Khodadadian; Pranay Sharma; Gauri Joshi; Siva Theja Maguluri (ICML, 2022)

Backward Curriculum Reinforcement Learning. - Kyungmin Ko; Sajad Khodadadian; Siva Theja Maguluri (CoRR, 2022)

Finite-Sample Analysis of Off-Policy Natural Actor-Critic With Linear Function Approximation. - Zaiwei Chen; Sajad Khodadadian; Siva Theja Maguluri (IEEE Control. Syst. Lett., 2022)

On linear and super-linear convergence of Natural Policy Gradient algorithm. - Sajad Khodadadian; Prakirt Raj Jhunjhunwala; Sushil Mahavir Varma; Siva Theja Maguluri (Syst. Control. Lett., 2022)

Finite-Sample Analysis of Two-Time-Scale Natural Actor-Critic Algorithm. - Sajad Khodadadian; Thinh T. Doan 001; Justin Romberg; Siva Theja Maguluri (IEEE Trans. Autom. Control., 2023)

Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise. - Shaan Ul Haque; Sajad Khodadadian; Siva Theja Maguluri (CoRR, 2024)

Sample complexity of Reinforcement Learning algorithms with a focus on policy space methods. - Sajad Khodadadian (2024)

A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging. - Sajad Khodadadian; Martin Zubeldia (CoRR, 2025)