On the approximation of vector-valued functions by samples. - Daniel Kressner; Tingting Ni; André Uschmajew (CoRR, 2023)

Interior Point Constrained Reinforcement Learning with Global Convergence Guarantees. - Tingting Ni; Maryam Kamgarpour (CoRR, 2023)

Convergence of a model-free entropy-regularized inverse reinforcement learning algorithm. - Titouan Renard; Andreas Schlaginhaufen; Tingting Ni; Maryam Kamgarpour (CDC, 2024)

A Safe Exploration Approach to Constrained Markov Decision Processes. - Tingting Ni; Maryam Kamgarpour (AISTATS, 2025)

A learning-based approach to stochastic optimal control under reach-avoid constraint. - Tingting Ni; Maryam Kamgarpour (HSCC, 2025)

On the approximation of vector-valued functions by volume sampling. - Daniel Kressner; Tingting Ni; André Uschmajew (J. Complex., 2025)

On characterization and existence of a constrained correlated equilibria in Markov games. - Tingting Ni; Anna M. Maddux; Maryam Kamgarpour (CoRR, 2025)