News
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 ...
CDC (2 papers): Wasserstein minimax control of ambiguous linear stochastic systems & Nonconvex optimization on the Stiefel manifold
The papers "Minimax Control of Ambiguous Linear Stochastic Systems Using the Wasserstein Metric", and "A Stochastic Consensus Method for Nonconvex Optimization on the Stiefel Manifold" have been ...
IROS: Learning-based distributionally robust motion control with Gaussian processes
The paper "Learning-based distributionally robust motion control with Gaussian processes", authored by Astghik Hakobyan, and Insoon Yang, has been accepted to the IEEE/RSJ International Conference on Intelligent ...
L4DC: Hamilton-Jacobi-Bellman Equations for Q-Learning in Continuous-Time
The paper "Hamilton-Jacobi-Bellman equations for Q-learning in continuous time", authored by Jeongho Kim, and Insoon Yang, has been accepted to the Conference on Learning for Dynamics and ...
