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)
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 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)
—The notion of meta-mining has appeared recently and extends the traditional meta-learning in two ways. First it does not learn meta-models that provide support only for the learning algorithm selection task but ones that support the whole data-mining process. In addition it abandons the so called black-box approach to algorithm description followed in(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)
Using matrix elasticity and cyclic stretch have been investigated for inducing mesenchymal stromal cell (MSC) differentiation towards the smooth muscle cell (SMC) lineage but not in combination. We hypothesized that combining lineage-specific stiffness with cyclic stretch would result in a significantly increased expression of SMC markers, compared to(More)
The nanoarchitecture and micromachinery of a cell can be leveraged to fabricate sophisticated cell-driven devices. This requires a coherent strategy to derive cell's mechanistic abilities, microconstruct, and chemical-texture towards such microtechnologies. For example, a microorganism's hydrophobic membrane encapsulating hygroscopic constituents allows it(More)