This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
We present a new run-time system for typed programming languages that supports object sharing in a distributed system. The key insight in this system is that the ability to distin...
Y. Charlie Hu, Weimin Yu, Alan L. Cox, Dan S. Wall...
During the development of car engines, regression models that are based on machine learning techniques are increasingly important for tasks which require a prediction of results i...
Policy search is a method for approximately solving an optimal control problem by performing a parametric optimization search in a given class of parameterized policies. In order ...
Given a hypergraph and a set of embedded functional dependencies, we investigate the problem of determining the conditions under which we can efficiently generate redundancy-free ...