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» The SDA Model: A Set Theory Approach
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NIPS
2000
13 years 10 months ago
Learning Continuous Distributions: Simulations With Field Theoretic Priors
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
Ilya Nemenman, William Bialek
SIGIR
2008
ACM
13 years 8 months ago
Personalized active learning for collaborative filtering
Collaborative Filtering (CF) requires user-rated training examples for statistical inference about the preferences of new users. Active learning strategies identify the most infor...
Abhay Harpale, Yiming Yang
SIGECOM
2006
ACM
143views ECommerce» more  SIGECOM 2006»
14 years 2 months ago
Braess's paradox in large random graphs
Braess’s Paradox is the counterintuitive but well-known fact that removing edges from a network with “selfish routing” can decrease the latency incurred by traffic in an eq...
Gregory Valiant, Tim Roughgarden
JAIR
2006
110views more  JAIR 2006»
13 years 8 months ago
Domain Adaptation for Statistical Classifiers
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Hal Daumé III, Daniel Marcu
ICPR
2002
IEEE
14 years 9 months ago
Incorporating Conditional Independence Assumption with Support Vector Machines to Enhance Handwritten Character Segmentation Per
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
Manolis Maragoudakis, Ergina Kavallieratou, Nikos ...