This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Rescaling is possibly the most popular approach to cost-sensitive learning. This approach works by rescaling the classes according to their costs, and it can be realized in differ...
Process monitoring refers to the task of detecting abnormal process operations resulting from the shift in the mean and/or the variance of one or more process variables. To success...
Recent text and speech processing applications such as speech mining raise new and more general problems related to the construction of language models. We present and describe in...
As genomic and proteomic data is collected from highthroughput methods on a daily basis, subcellular components are identified and their in vitro behavior is characterized. Howev...
Salim Khan, William Gillis, Carl Schmidt, Keith De...