Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...
Due to its occurrence in engineering domains and implications for natural learning, the problem of utilizing unlabeled data is attracting increasing attention in machine learning....
This paper describes the design and implementation of virtual memory management within the CMU Mach Operating System and the experiences gained by the Mach kernel group in porting...
Richard F. Rashid, Avadis Tevanian, Michael Young,...
Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...