We consider an online learning setting where at each time step the decision maker has to choose how to distribute the future loss between k alternatives, and then observes the los...
Asian options, basket options and spread options have been extensively studied in literature. However, few papers deal with the problem of pricing general Asian basket spread opti...
Accurate network modeling is critical to the design of network protocols. Traditional modeling approaches, such as Discrete Time Markov Chains (DTMC) are limited in their ability ...
The design, development, and use of complex systems models raises a unique class of challenges and potential pitfalls, many of which are commonly recurring problems. Over time, res...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...