ICDE
2012
IEEE
12 years 2 months ago
2012
IEEE
—With the exponential growth in the amount of data that is being generated in recent years, there is a pressing need for applying machine learning algorithms to large data sets. ...
ECOOP
2011
Springer
13 years 6 days ago
2011
Springer
Abstract. The information of execution frequencies of virtual call targets is valuable for program analyses and optimizations of object-oriented programs. However, to obtain this i...
AAAI
2011
13 years 13 days ago
2011
End-user interactive machine learning is a promising tool for enhancing human productivity and capabilities with large unstructured data sets. Recent work has shown that we can cr...
AIED
2011
Springer
13 years 4 months ago
2011
Springer
The Pedagogical Assessment Workflow System (PAWS) is a new workflow-based pedagogical assessment framework that enables the efficient and robust integration of diverse datasets for...
ICMLA
2003
14 years 1 months ago
2003
– Discretization is a process of converting a continuous attribute into an attribute that contains small number of distinct values. One of the major reasons for discretizing an a...
NIPS
2001
14 years 1 months ago
2001
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
NIPS
2004
14 years 1 months ago
2004
Machine learning is often used to automatically solve human tasks. In this paper, we look for tasks where machine learning algorithms are not as good as humans with the hope of ga...
HIS
2004
14 years 1 months ago
2004
The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Using a classifier based on machine learning techniques ...
EACL
2006
ACL Anthology
14 years 1 months ago
2006
ACL Anthology
This paper deals with the problem of recognizing and extracting acronymdefinition pairs in Swedish medical texts. This project applies a rule-based method to solve the acronym rec...
DAGSTUHL
2004
14 years 1 months ago
2004
Next to prediction accuracy, the interpretability of models is one of the fundamental criteria for machine learning algorithms. While high accuracy learners have intensively been e...