Background: Techniques for measuring protein abundance are rapidly advancing and we are now in a situation where we anticipate many protein abundance data sets will be available i...
Eric Z. Yu, Anne E. Counterman Burba, Mark Gerstei...
Background: In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms suc...
Yi Lu, Shiyong Lu, Farshad Fotouhi, Youping Deng, ...
This paper gives an overview of two middleware systems that have been developed over the last 6 years to address the challenges involved in developing parallel and distributed imp...
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...