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» Information Theory, Inference, and Learning Algorithms
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TRS
2008
13 years 7 months ago
A Model of User-Oriented Reduct Construction for Machine Learning
An implicit assumption of many machine learning algorithms is that all attributes are of the same importance. An algorithm typically selects attributes based solely on their statis...
Yiyu Yao, Yan Zhao, Jue Wang, Suqing Han
JCDL
2006
ACM
161views Education» more  JCDL 2006»
14 years 1 months ago
Learning metadata from the evidence in an on-line citation matching scheme
Citation matching, or the automatic grouping of bibliographic references that refer to the same document, is a data management problem faced by automatic digital libraries for sci...
Isaac G. Councill, Huajing Li, Ziming Zhuang, Sand...
SAGA
2001
Springer
14 years 11 days ago
Stochastic Finite Learning
Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...
Thomas Zeugmann
ICML
2010
IEEE
13 years 9 months ago
Budgeted Nonparametric Learning from Data Streams
We consider the problem of extracting informative exemplars from a data stream. Examples of this problem include exemplarbased clustering and nonparametric inference such as Gauss...
Ryan Gomes, Andreas Krause
COOPIS
2003
IEEE
14 years 1 months ago
Learning to Invoke Web Forms
Emerging Web standards promise a network of heterogeneous yet interoperable Web Services. Web Services would greatly simplify the development of many kinds of information agents a...
Nicholas Kushmerick