Phong Nguyen

Learn More
1 Abstract This chapter describes a principled approach to meta-learning that has three distinctive features. First, whereas most previous work on meta-learning focused exclusively on the learning task, our approach applies meta-learning to the full knowledge discovery process and is thus more aptly referred to as meta-mining. Second, traditional(More)
Antimicrobial resistance is a major global health threat. In the European Union an estimated 25,000 deaths occur annually secondary to multi-drug-resistant infections [1]. No reliable estimates for developing countries exist, but figures are likely to be higher. Strategies to contain antimicrobial resistance were comprehensively set forth by the World(More)
The Data Mining OPtimization Ontology (DMOP) has been developed to support informed decision-making at various choice points of the data mining process. The ontology can be used by data miners and deployed in ontology-driven information systems. The primary purpose for which DMOP has been developed is the automation of algorithm and model selection through(More)
We would like to thank Gary Fields and Andrew Foster for useful discussion and comments. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank, its Executive Directors, or the countries they represent, nor do they necessarily represent the views(More)
The notion of meta-mining has appeared recently and extends traditional meta-learning in two ways. First it provides support for the whole data-mining process. Second it pries open the so called algorithm black-box approach where algorithms and workflows also have descriptors. With the availability of descriptors both for datasets and data-mining workflows(More)
High Efficiency Video Coding (HEVC) or H.265Standard fulfills the demand of high resolution video storage and transmission since it achieves high compression ratio. However, it requires a huge amount of calculation. Since Motion Estimation (ME) block composes about 80% of calculation load of HEVC, there are a lot of researches to reduce the computation(More)
Recommendation systems often rely on point-wise loss metrics such as the mean squared error. However, in real recommendation settings only few items are presented to a user. This observation has recently encouraged the use of rank-based metrics. LambdaMART is the state-of-the-art algorithm in learning to rank which relies on such a metric. Motivated by the(More)