News
JMLR: Hamilton-Jacobi deep Q-learning
The paper "Hamilton-Jacobi deep Q-learning for deterministic continuous-time systems with Lipschitz continuous controls" has been accepted for publication in the Journal of Machine Learning Research (JMLR). It ...
T-RO: Distributionally robust motion control using CVaR
The paper "Wasserstein distributionally robust motion control for collision avoidance using conditional value-at-risk" has been accepted for publication in the IEEE Transactions on Robotics. It presents a ...
CDC (2 papers): Anderson acceleration for POMDPs, Distributionally robust control in learning-enabled environments
The papers "On Anderson Acceleration for Partially Observable Markov Decision Processes", and "Improving the Distributional Robustness of Risk-Aware Controllers in Learning-Enabled Environments" have been accepted to the ...
TAC: Data-driven Wasserstein distributionally robust stochastic control
The paper "Wasserstein distributionally robust stochastic control: A data-driven approach," authored by Insoon Yang, has been accepted for publication in the IEEE Transactions on Automatic Control. This ...
JOTA: Convex optimization approach to dynamic programming in continuous state and action spaces
The paper "A convex optimization approach to dynamic programming in continuous state and action spaces," authored by Insoon Yang, has been accepted for publication in the Journal ...
ECE M.S. Thesis Award: Astghik Hakobyan’s “Risk-Aware Distributionally Robust Optimization for Learning-Based Autonomous Systems”
Astghik Hakobyan wins the best ECE M.S. thesis award. Her thesis, entitled "Risk-Aware Distributionally Robust Optimization for Learning-Based Autonomous Systems," has been evaluated as "excellent, very creative ...
