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JMLR
2010
132views more  JMLR 2010»
14 years 4 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...
JMLR
2010
107views more  JMLR 2010»
14 years 4 months ago
Learning Instance-Specific Predictive Models
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
Shyam Visweswaran, Gregory F. Cooper
AIEDU
2005
185views more  AIEDU 2005»
14 years 9 months ago
A Bayesian Student Model without Hidden Nodes and its Comparison with Item Response Theory
The Bayesian framework offers a number of techniques for inferring an individual's knowledge state from evidence of mastery of concepts or skills. A typical application where ...
Michel C. Desmarais, Xiaoming Pu
IDA
2010
Springer
14 years 11 months ago
Data Mining for Modeling Chiller Systems in Data Centers
We present a data mining approach to model the cooling infrastructure in data centers, particularly the chiller ensemble. These infrastructures are poorly understood due to the lac...
Debprakash Patnaik, Manish Marwah, Ratnesh K. Shar...
INTEGRATION
2007
107views more  INTEGRATION 2007»
14 years 9 months ago
Power and electromagnetic analysis: Improved model, consequences and comparisons
Since their publication in 1998 and 2001 respectively, Power and Electromagnetic Analysis (SPA, DPA, EMA) have been successfully used to retrieve secret information stored in cryp...
Eric Peeters, François-Xavier Standaert, Je...