Abstract. The technique of flattening nested data parallelism combines all the independent operations in nested apply-to-all constructs and generates large amounts of potential pa...
Daniel W. Palmer, Jan Prins, Siddhartha Chatterjee...
The standard kNN algorithm suffers from two major drawbacks: sensitivity to the parameter value k, i.e., the number of neighbors, and the use of k as a global constant that is ind...
Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
We introduce a multi-stage ensemble framework, ErrorDriven Generalist+Expert or Edge, for improved classification on large-scale text categorization problems. Edge first trains a ...
This paper describes an application of statistical co-occurrence techniques that built on top of a probabilistic image annotation framework is able to increase the precision of an ...
Ainhoa Llorente, Simon E. Overell, Haiming Liu 000...