S. Amani, T. Lattimore, A. Gyorgy, L. F. Yang, "Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost", International Conference on Machine Learning (ICML), 2023.
S. Amani, L. F. Yang, C.-A. Cheng, "Provably Efficient Lifelong Reinforcement Learning with Linear Representation", International Conference on Learning Representations (ICLR), 2023.
S. Amani, L. F. Yang, "Doubly Pessimistic Algorithms for Strictly Safe Off-Policy Optimization", Annual Conference on Information Sciences and Systems (CISS), 2022.
S. Amani, C. Thrampoulidis, "UCB-based Algorithms for Multinomial Logistic Regression Bandits", Advances in Neural Information Processing Systems (NeurIPS), 2021.
S. Amani, C. Thrampoulidis, L. F. Yang, "Safe Reinforcement Learning with Linear Function Approximation", International Conference on Machine Learning (ICML), 2021.
S. Amani, M. Alizadeh, C. Thrampoulidis, "Regret Bound for Safe Gaussian Process Bandit Optimization", IEEE International Symposium on Information Theory (ISIT), 2021.
S. Amani, C. Thrampoulidis, "Decentralized Multi-Agent Linear Bandits with Safety Constraints", AAAI Conference on Artificial Intelligence (AAAI), 2021.
A. Moradipari, S. Amani, M. Alizadeh, C. Thrampoulidis, "Safe Linear Thompson Sampling with Side Information", IEEE Transactions on Signal Processing, 2021.
S. Amani, M. Alizadeh, C. Thrampoulidis, "Generalized Linear Bandits with Safety Constraints", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020.
S. Amani, M. Alizadeh, C. Thrampoulidis, "Linear Stochastic Bandits Under Safety Constraints", Advances in Neural Information Processing Systems (NeurIPS), 2019.