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» Learning Instance-Specific Predictive Models
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UAI
2000
13 years 10 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
GROUP
2010
ACM
13 years 6 months ago
Design, implementation, and evaluation of an approach for determining when programmers are having difficulty
Previous research has motivated the idea of automatically determining when programmers are having difficulty, provided an initial algorithm (unimplemented in an actual system), an...
Jason Carter, Prasun Dewan
SIGMOD
2012
ACM
242views Database» more  SIGMOD 2012»
11 years 11 months ago
Dynamic management of resources and workloads for RDBMS in cloud: a control-theoretic approach
As cloud computing environments become explosively popular, dealing with unpredictable changes, uncertainties, and disturbances in both systems and environments turns out to be on...
Pengcheng Xiong
TNN
2008
93views more  TNN 2008»
13 years 8 months ago
Towards the Optimal Design of Numerical Experiments
This paper addresses the problem of the optimal design of numerical experiments for the construction of nonlinear surrogate models. We describe a new method, called learner disagre...
S. Gazut, J.-M. Martinez, Gérard Dreyfus, Y...
JMLR
2010
104views more  JMLR 2010»
13 years 3 months ago
How to Explain Individual Classification Decisions
After building a classifier with modern tools of machine learning we typically have a black box at hand that is able to predict well for unseen data. Thus, we get an answer to the...
David Baehrens, Timon Schroeter, Stefan Harmeling,...