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» Learning Mixtures of DAG Models
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ICML
2009
IEEE
14 years 10 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani
NIPS
2004
13 years 11 months ago
Active Learning for Anomaly and Rare-Category Detection
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional st...
Dan Pelleg, Andrew W. Moore
AVSS
2007
IEEE
14 years 4 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen
NIPS
2007
13 years 11 months ago
Learning with Tree-Averaged Densities and Distributions
We utilize the ensemble of trees framework, a tractable mixture over superexponential number of tree-structured distributions [1], to develop a new model for multivariate density ...
Sergey Kirshner
ESANN
2001
13 years 11 months ago
A divide-and-conquer learning architecture for predicting unknown motion
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
Patrice Wira, Jean-Philippe Urban, Julien Gresser