![[ICML] Accelerated gradient methods for geodesically convex optimization](http://coregroup.snu.ac.kr/wp-content/uploads/2022/05/Screen-Shot-2022-05-16-at-9.54.13-AM-360x220.png)
[ICML] Accelerated gradient methods for geodesically convex optimization
The paper "Accelerated gradient methods for geodesically convex optimization: Tractable algorithms and convergence analysis" has been accepted to the International Conference on Machine Learning (ICML). Accelerated gradient methods for geodesically convex optimization: Tractable algorithms and convergence ...
![[TAC] Maximum entropy optimal control in continuous time](http://coregroup.snu.ac.kr/wp-content/uploads/2022/04/Screen-Shot-2022-04-15-at-4.11.58-PM-360x220.png)
[TAC] Maximum entropy optimal control in continuous time
The paper "Maximum entropy optimal control of continuous-time dynamical systems" has been accepted for publication in the IEEE Transactions on Automatic Control. Maximum entropy optimal control of continuous-time dynamical systems by Jeongho Kim, and Insoon Yang ...
![[M3AS] Nonconvex optimization on the Stiefel manifold](http://coregroup.snu.ac.kr/wp-content/uploads/2022/04/Screen-Shot-2022-04-15-at-3.52.40-PM-360x220.jpg)
[M3AS] Nonconvex optimization on the Stiefel manifold
The paper "Stochastic consensus dynamics for nonconvex optimization on the Stiefel manifold: Mean-field limit and convergence" has been accepted for publication in Mathematical Models and Methods in Applied Sciences (M3AS). Stochastic consensus dynamics for nonconvex optimization ...
![[TAC] Risk-sensitive safety analysis using CVaR](http://coregroup.snu.ac.kr/wp-content/uploads/2021/11/Screen-Shot-2021-11-16-at-1.43.26-PM-360x220.png)
[TAC] Risk-sensitive safety analysis using CVaR
The paper "Risk-sensitive safety analysis using conditional value-at-risk" has been accepted for publication in the IEEE Transactions on Automatic Control. Risk-sensitive safety analysis using conditional value-at-risk by Margaret P. Chapman, Riccardo Bonalli, Kevin M. Smith, Insoon Yang, Marco ...
![[JMLR] Hamilton-Jacobi deep Q-learning](http://coregroup.snu.ac.kr/wp-content/uploads/2021/09/Screen-Shot-2021-09-02-at-5.00.55-PM-360x220.png)
[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 aims to extend the idea of deep Q-networks (DQN) ...