Comprehending action preconditions and effects is an essential step in modeling the dynamics of the world. In this paper, we express the semantics of precondition relations extrac...
S. R. K. Branavan, Nate Kushman, Tao Lei, Regina B...
Abstract. We describe a probabilistic model, implemented as a dynamic Bayesian network, that can be used to predict nucleosome positioning along a chromosome based on one or more g...
Sheila M. Reynolds, Zhiping Weng, Jeff A. Bilmes, ...
This paper proposes a dynamic cache repartitioning technique that enhances compositionality on platforms executing media applications with multiple utilization scenarios. The repa...
Anca Mariana Molnos, Marc J. M. Heijligers, Sorin ...
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
We study graphical modeling in the case of stringvalued random variables. Whereas a weighted finite-state transducer can model the probabilistic relationship between two strings, ...