Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
It would be useful if software engineers/instructors could be aware that remote team members/students are having difficulty with their programming tasks. We have developed an appr...
This paper presents improved approximation algorithms for the problem of multiprocessor scheduling under uncertainty (SUU), in which the execution of each job may fail probabilist...
Christopher Y. Crutchfield, Zoran Dzunic, Jeremy T...
We propose an active set algorithm to solve the convex quadratic programming (QP) problem which is the core of the support vector machine (SVM) training. The underlying method is ...
Introducing technology as a sustainable means of creating, connecting, and collaborating introduces the need to carefully consider subtle aspects of deployment strategies and supp...
Yagiz Onat Yazir, Katherine Gunion, Christopher Pe...