Learning and Decision Systems Lab

Jul. 2025. Three papers have been accepted to IEEE Conference on Decision and Control (CDC).

Mar. 2025. "Approximate Thompson sampling for learning linear quadratic regulators with $O(\sqrt{T})$ regret" has been accepted to Learning for Dynamics and Control (L4DC). (Oral)

Apr. 2024. "Wasserstein distributionally robust control of partially observable linear stochastic systems" has been accepted to IEEE Transactions on Automatic Control.

Mar. 2024. "On task-relevant loss functions in meta-reinforcement learning" has been accepted to Learning for Dynamics and Control (L4DC).

Jan. 2024. "Anderson acceleration for partially observable Markov decision processes: A maximum entropy approach" has been accepted to Automatica.

Dec. 2023. "Risk-aware Wasserstein distributionally robust control of vessels in natural waterways" has been accepted to IEEE Transactions on Control Systems Technology.

Sep. 2023. "Convergence analysis of ODE models for accelerated first-order methods via positive semidefinite kernels" has been accepted to Advances in Neural Information Processing Systems (NeurIPS).

Aug. 2023. Astghik Hakobyan received her Ph.D. and was honored with the Distinguished ECE Ph.D. Dissertation Award.

Aug. 2023. "Control of fab lifters via deep reinforcement learning: A semi-MDP approach" has been accepted to IEEE Transactions on Automation Science and Engineering.

Apr. 2023. "Unifying Nesterov's accelerated gradient methods for convex and strongly convex objective functions" has been accepted to International Conference on Machine Learning (ICML). (Oral)