As underlying infrastructure of cloud computing platform, datacenter is seriously underutilized, however, its operating costs is high. In this paper, we implement virtual machines placement algorithm in CloudSim using constraint programming approach. We first formulate the problem of virtual machines placement in virtualized datacenters as a variant of multi-dimensions bin packing problem, and ...

The relevance vector machine (RVM) (Tipping, 2001) encapsulates a sparse probabilistic model for machine learning tasks. Like support vector machines, use of the kernel trick allows modelling in high dimensional feature spaces to be achieved at low computational cost. However, sparsity is controlled not just by the automatic relevance determination (ARD) prior but also by the choice of basis fu...

Scheduling of multiple parallel machines in the face of sequence dependent setups and downstream considerations is a hard problem. No single efficient algorithm is guaranteed to produce optimal results. We describe a solution for an instance of this problem, in the domain of paper manufacturing. The problem has additional job machine restrictions and fixed costs of assigning jobs to machines. W...

| The PARADIGM (PARAllelizing compiler for DIstributed-memory General-purpose Multicomputers) project at the University of Illinois provides a fully automated means to parallelize programs, written in a serial programming model, for execution on distributed-memory multicomputers. To provide eecient execution, PARADIGM automatically performs various optimizations to reduce the overhead and idle ...

As the number of applications that use machine learning algorithms increases, the need for labeled data useful for training such algorithms intensifies. Getting labels typically involves employing humans to do the annotation, which directly translates to training and working costs. Crowdsourcing platforms have made labeling cheaper and faster, but they still involve significant costs, especiall...

OBJECTIVES To determine whether a home-based care coordination program focused on medication self-management would affect the cost of care to the Medicare program and whether the addition of technology, a medication-dispensing machine, would further reduce cost. DESIGN Randomized, controlled, three-arm longitudinal study. SETTING Participant homes in a large Midwestern urban area. PARTICI...

Decision makers, such as doctors, make crucial decisions such as recommending treatments to patients on a daily basis. Such decisions typically involve careful assessment of the subject’s condition, analyzing the costs associated with the possible actions, and the nature of the consequent outcomes. Further, there might be costs associated with the assessment of the subject’s condition itself (e...

Gene expression profiling by microarray technology has been successfully applied to classification and diagnostic prediction of cancers. Various machine learning and data mining methods are currently used for classifying gene expression data. However, these methods have not been developed to address the specific requirements of gene microarray analysis. First, microarray data is characterized b...

Cloud computing is becoming more and more popular in computing infrastructure and it also introduces new security problems. For example, a physical server shared by many virtual machines can be taken over by an attacker if the virtual machine monitor is compromised through one of the virtual machines. Thus, collocating with vulnerable virtual machines, or “bad neighbours”, on the same physical ...

This paper contributes a study of methods for integrating human expert knowledge with machine learning approaches for determining phonetic similarity of word pairs. A method is proposed which allows a human to provide a structure for the edit costs that are based around a phonetically-motivated model of phoneme sound groups, and the machine to determine precise values for these costs within two...