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» Bounding the cost of learned rules
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SIGECOM
2010
ACM
147views ECommerce» more  SIGECOM 2010»
14 years 1 months ago
Socially desirable approximations for Dodgson's voting rule
In 1876 Charles Lutwidge Dodgson suggested the intriguing voting rule that today bears his name. Although Dodgson’s rule is one of the most well-studied voting rules, it suffers...
Ioannis Caragiannis, Christos Kaklamanis, Nikos Ka...
JAIR
2010
145views more  JAIR 2010»
13 years 6 months ago
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Tobias Lang, Marc Toussaint
ICDM
2006
IEEE
89views Data Mining» more  ICDM 2006»
14 years 2 months ago
On the Lower Bound of Local Optimums in K-Means Algorithm
The k-means algorithm is a popular clustering method used in many different fields of computer science, such as data mining, machine learning and information retrieval. However, ...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung
AAAI
1998
13 years 9 months ago
Learning Investment Functions for Controlling the Utility of Control Knowledge
The utility problem occurs when the cost of the acquired knowledge outweighs its bene ts. When the learner acquires control knowledge for speeding up a problem solver, the bene t ...
Oleg Ledeniov, Shaul Markovitch
PKDD
2010
Springer
152views Data Mining» more  PKDD 2010»
13 years 6 months ago
Online Knowledge-Based Support Vector Machines
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbee...