We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...
With the advent of next-generation DNA sequencing machines, there is an increasing need for the development of computational tools that can anchor accurately and expediently the m...
We introduce a new model of molecular computation that we call the sticker model. Like many previous proposals it makes use of DNA strands as the physical substrate in which infor...
Sam T. Roweis, Erik Winfree, Richard Burgoyne, Nic...
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
1 This paper provides a new, generalized approach to the problem of encoding information as vectors of binary digits. We furnish a formal definition for the Boolean constrained enc...