Modern machine learning techniques provide robust approaches for data-driven modeling and critical information extraction, while human experts hold the advantage of possessing hig...
Phylogenetic hidden Markov models (phylo-HMMs) have recently been proposed as a means for addressing a multispecies version of the ab initio gene prediction problem. These models ...
Abstract. This paper presents PerWiz, a performance prediction tool for improving the performance of message passing programs. PerWiz focuses on locating where a significant impro...
The circular sensing model has been widely used to estimate performance of sensing applications in existing analysis and simulations. While this model provides valuable high-level...
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...