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PAMI
2006
127views more  PAMI 2006»
13 years 9 months ago
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Martin H. C. Law, Anil K. Jain
SIGCSE
2008
ACM
110views Education» more  SIGCSE 2008»
13 years 9 months ago
Innovating our self image
ion." These images do not foster collaboration with other fields and do not excite the curiosity of young people. In this session, Astrachan and Denning will discuss what they...
Owen L. Astrachan, Peter J. Denning
SYNTHESE
2008
84views more  SYNTHESE 2008»
13 years 9 months ago
Model structure adequacy analysis: selecting models on the basis of their ability to answer scientific questions
Models carry the meaning of science. This puts a tremendous burden on the process of model selection. In general practice, models are selected on the basis of their relative goodne...
Mark L. Taper, David F. Staples, Bradley B. Shepar...
IJSN
2007
94views more  IJSN 2007»
13 years 9 months ago
On security proof of McCullagh?Barreto's key agreement protocol and its variants
: McCullagh and Barreto presented an identity-based authenticated key agreement protocol in CT-RSA 2005. Their protocol was found to be vulnerable to a key-compromise impersonation...
Zhaohui Cheng, Liqun Chen
JMLR
2007
58views more  JMLR 2007»
13 years 9 months ago
Distances between Data Sets Based on Summary Statistics
The concepts of similarity and distance are crucial in data mining. We consider the problem of defining the distance between two data sets by comparing summary statistics compute...
Nikolaj Tatti