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ICML
2009
IEEE
16 years 5 months ago
Unsupervised hierarchical modeling of locomotion styles
This paper describes an unsupervised learning technique for modeling human locomotion styles, such as distinct related activities (e.g. running and striding) or variations of the ...
Wei Pan, Lorenzo Torresani
ICML
1997
IEEE
16 years 5 months ago
Characterizing the generalization performance of model selection strategies
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
Dale Schuurmans, Lyle H. Ungar, Dean P. Foster
SIGSOFT
2007
ACM
16 years 5 months ago
Recommending random walks
We improve on previous recommender systems by taking advantage of the layered structure of software. We use a random-walk approach, mimicking the more focused behavior of a develo...
Zachary M. Saul, Vladimir Filkov, Premkumar T. Dev...
WWW
2007
ACM
16 years 5 months ago
Hierarchical, perceptron-like learning for ontology-based information extraction
Recent work on ontology-based Information Extraction (IE) has tried to make use of knowledge from the target ontology in order to improve semantic annotation results. However, ver...
Yaoyong Li, Kalina Bontcheva
WWW
2007
ACM
16 years 5 months ago
U-REST: an unsupervised record extraction system
In this paper, we describe a system that can extract record structures from web pages with no direct human supervision. Records are commonly occurring HTML-embedded data tuples th...
Yuan Kui Shen, David R. Karger