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103
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IPL
2010
92views more  IPL 2010»
15 years 1 months ago
Learning parities in the mistake-bound model
We study the problem of learning parity functions that depend on at most k variables (kparities) attribute-efficiently in the mistake-bound model. We design a simple, deterministi...
Harry Buhrman, David García-Soriano, Arie M...
ML
2008
ACM
134views Machine Learning» more  ML 2008»
15 years 2 months ago
Multilabel classification via calibrated label ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operat...
Johannes Fürnkranz, Eyke Hüllermeier, En...
133
Voted
PERCOM
2003
ACM
15 years 7 months ago
Recognition of Human Activity through Hierarchical Stochastic Learning
Seeking to extend the functional capability of the elderly, we explore the use of probabilistic methods to learn and recognise human activity in order to provide monitoring suppor...
Sebastian Lühr, Hung Hai Bui, Svetha Venkates...
ICML
2000
IEEE
15 years 7 months ago
Mutual Information in Learning Feature Transformations
We present feature transformations useful for exploratory data analysis or for pattern recognition. Transformations are learned from example data sets by maximizing the mutual inf...
Kari Torkkola, William M. Campbell
ML
2007
ACM
15 years 2 months ago
Learning deterministic context free grammars: The Omphalos competition
This paper describes the winning entry to the Omphalos context free grammar learning competition. Our approach integrates an information theoretic constituent likelihood measure to...
Alexander Clark