1 citations · 2 across the 4 of their papers we have counts for
5 papers
A unified algorithm framework for mean-variance optimization in discounted Markov decision processes
Shuai Ma, Xiaoteng Ma, Li Xia
This paper studies the risk-averse mean-variance optimization in infinite-horizon discounted Markov decision processes (MDPs). The involved variance metric concerns reward variabil…
First- and Second-Moment Constrained Gaussian Channels
Shuai Ma, Michèle Wigger
This paper studies the channel capacity of intensity-modulation direct-detection (IM/DD) visible light communication (VLC) systems under both optical and electrical power constrain…
Variance-Based Risk Estimations in Markov Processes via Transformation with State Lumping
Shuai Ma, Jia Yuan Yu
Variance plays a crucial role in risk-sensitive reinforcement learning, and most risk measures can be analyzed via variance. In this paper, we consider two law-invariant risks as e…
A Scheme for Dynamic Risk-Sensitive Sequential Decision Making
Shuai Ma, Jia Yuan Yu, Ahmet Satir
We present a scheme for sequential decision making with a risk-sensitive objective and constraints in a dynamic environment. A neural network is trained as an approximator of the m…
State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning
Shuai Ma, Jia Yuan Yu
In the framework of MDP, although the general reward function takes three arguments-current state, action, and successor state; it is often simplified to a function of two argument…