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» Closed Sets for Labeled Data
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117
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ICML
2005
IEEE
16 years 2 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
79
Voted
ESA
2010
Springer
220views Algorithms» more  ESA 2010»
15 years 2 months ago
Data Structures for Storing Small Sets in the Bitprobe Model
abstract appeared in Proc. 24th Annual Symposium of Computational Geometry (SoCG), 2008, pp. 338-345. S. Shannigrahi and S. P. Pal, "Efficient Prufer-like Coding and Counting ...
Jaikumar Radhakrishnan, Smit Shah 0001, Saswata Sh...
129
Voted
IDA
2005
Springer
15 years 7 months ago
Learning from Ambiguously Labeled Examples
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Eyke Hüllermeier, Jürgen Beringer
126
Voted
JIIS
2008
133views more  JIIS 2008»
15 years 1 months ago
Maintaining frequent closed itemsets over a sliding window
In this paper, we study the incremental update of Frequent Closed Itemsets (FCIs) over a sliding window in a high-speed data stream. We propose the notion of semi-FCIs, which is to...
James Cheng, Yiping Ke, Wilfred Ng
122
Voted
ICSE
2004
IEEE-ACM
16 years 1 months ago
Automated Generation of Test Programs from Closed Specifications of Classes and Test Cases
Most research on automated specification-based software testing has focused on the automated generation of test cases. Before a software system can be tested, it must be set up ac...
Wee Kheng Leow, Siau-Cheng Khoo, Yi Sun