134 search results - page 10 / 27 » Experimental analysis of privacy loss in DCOP algorithms |
CORR
2011
Springer
14 years 1 months ago
2011
Springer
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
PAMI
2008
14 years 9 months ago
2008
In this paper, we develop a new effective multiple kernel learning algorithm. First, we map the input data into m different feature spaces by m empirical kernels, where each genera...
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SDMW
2009
Springer
15 years 4 months ago
2009
Springer
In this paper we investigate the feasibility and efficiency of mapping XML data and access control policies onto relational and native XML databases for storage and querying. We de...
IMC
2010
ACM
14 years 7 months ago
2010
ACM
Online advertising supports many Internet services, such as search, email, and social networks. At the same time, there are widespread concerns about the privacy loss associated w...
NIPS
2007
14 years 11 months ago
2007
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...