The typical workload in a database system consists of a mixture of multiple queries of different types, running concurrently and interacting with each other. Hence, optimizing per...
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Query reformulation modifies the original query with the aim of better matching the vocabulary of the relevant documents, and consequently improving ranking effectiveness. Previou...
In this work, we propose a new robust and edge-preserving superresolution algorithm to simultaneously estimate all frames of a sequence. The new algorithm is based on the regulari...
Abstract. In this work, we propose a method which can extract critical points on a face using both location and texture information. This new approach can automatically learn featu...
Mustafa Berkay Yilmaz, Hakan Erdogan, Mustafa Unel