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» Learning aspect models with partially labeled data
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CSFW
2009
IEEE
13 years 11 months ago
Authentication without Elision: Partially Specified Protocols, Associated Data, and Cryptographic Models Described by Code
Specification documents for real-world authentication protocols typically mandate some aspects of a protocol's behavior but leave other features optional or undefined. In add...
Phillip Rogaway, Till Stegers
NIPS
2008
13 years 8 months ago
Generative and Discriminative Learning with Unknown Labeling Bias
We apply robust Bayesian decision theory to improve both generative and discriminative learners under bias in class proportions in labeled training data, when the true class propo...
Miroslav Dudík, Steven J. Phillips
ICML
1999
IEEE
14 years 8 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
ICCV
2009
IEEE
15 years 11 days ago
TagProp: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation
Image auto-annotation is an important open problem in computer vision. For this task we propose TagProp, a discriminatively trained nearest neighbor model. Tags of test images a...
Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek...
JMLR
2010
102views more  JMLR 2010»
13 years 2 months ago
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels
Estimating the error rates of classifiers or regression models is a fundamental task in machine learning which has thus far been studied exclusively using supervised learning tech...
Pinar Donmez, Guy Lebanon, Krishnakumar Balasubram...