We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
In some classification problems, like the detection of illnesses in patients, classes are very unbalanced and the misclassification costs for different classes vary significantly....
Vector Space Model (VSM) has been at the core of information retrieval for the past decades. VSM considers the documents as vectors in high dimensional space. In such a vector spa...
Similarity search has been proved suitable for searching in very large collections of unstructured data objects. We are interested in efficient parallel query processing under si...
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...