120 citations · 370 across the 36 of their papers we have counts for
7 papers · 1 filter
Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs
Yeoneung Kim, Insoon Yang, Kwang-Sung Jun
In online learning problems, exploiting low variance plays an important role in obtaining tight performance guarantees yet is challenging because variances are often not known a pr…
Training Wasserstein GANs without gradient penalties
Dohyun Kwon, Yeoneung Kim, Guido Montúfar +1
We propose a stable method to train Wasserstein generative adversarial networks. In order to enhance stability, we consider two objective functions using the -transform based on…
Infusing model predictive control into meta-reinforcement learning for mobile robots in dynamic environments
Jaeuk Shin, Astghik Hakobyan, Mingyu Park +3
The successful operation of mobile robots requires them to adapt rapidly to environmental changes. To develop an adaptive decision-making tool for mobile robots, we propose a novel…
Distributionally robust risk map for learning-based motion planning and control: A semidefinite programming approach
Astghik Hakobyan, Insoon Yang
This paper proposes a novel safety specification tool, called the distributionally robust risk map (DR-risk map), for a mobile robot operating in a learning-enabled environment. Gi…
On Anderson acceleration for partially observable Markov decision processes
Melike Ermis, Mingyu Park, Insoon Yang
This paper proposes an accelerated method for approximately solving partially observable Markov decision process (POMDP) problems offline. Our method carefully combines two existin…
Distributional robustness in minimax linear quadratic control with Wasserstein distance
Kihyun Kim, Insoon Yang
To address the issue of inaccurate distributions in practical stochastic systems, a minimax linear-quadratic control method is proposed using the Wasserstein metric. Our method aim…
Risk-sensitive safety analysis using Conditional Value-at-Risk
Margaret P. Chapman, Riccardo Bonalli, Kevin M. Smith +3
This paper develops a safety analysis method for stochastic systems that is sensitive to the possibility and severity of rare harmful outcomes. We define risk-sensitive safe sets a…