We consider situations in which a decision-maker with a fixed budget faces a sequence of options, each with a cost and a value, and must select a subset of them online so as to ma...
Moshe Babaioff, Nicole Immorlica, David Kempe, Rob...
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...
In this paper, we study the problem of scheduling parallel loops at compile-time for a heterogeneous network of machines. We consider heterogeneity in three aspects of parallel pr...
Activity recognition is a hot topic in context-aware computing. In activity recognition, machine learning techniques have been widely applied to learn the activity models from lab...
In this paper we propose a novel scheduling framework for a real-timeenvironmentthat experiences dynamic changes. Thisframework is capable of adjusting the system workload in incr...