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» Semi-supervised Learning from General Unlabeled Data
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KDD
2005
ACM
168views Data Mining» more  KDD 2005»
14 years 8 months ago
Nomograms for visualizing support vector machines
We propose a simple yet potentially very effective way of visualizing trained support vector machines. Nomograms are an established model visualization technique that can graphica...
Aleks Jakulin, Martin Mozina, Janez Demsar, Ivan B...
CIKM
2009
Springer
14 years 2 months ago
Networks, communities and kronecker products
Emergence of the web and online computing applications gave rise to rich large scale social activity data. One of the principal challenges then is to build models and understandin...
Jure Leskovec
ICPR
2010
IEEE
13 years 6 months ago
Boosting Bayesian MAP Classification
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...
KDD
2008
ACM
128views Data Mining» more  KDD 2008»
14 years 8 months ago
Scaling up text classification for large file systems
: We combine the speed and scalability of information retrieval with the generally superior classification accuracy offered by machine learning, yielding a two-phase text classifie...
George Forman, Shyamsundar Rajaram
PLDI
2010
ACM
14 years 5 months ago
Complete Functional Synthesis
Synthesis of program fragments from specifications can make programs easier to write and easier to reason about. To integrate synthesis into programming languages, synthesis algor...
Viktor Kuncak, Mika l Mayer, Ruzica Piskac, Philip...