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IPMI
2009
Springer
16 years 6 months ago
Marginal Space Learning for Efficient Detection of 2D/3D Anatomical Structures in Medical Images
Recently, marginal space learning (MSL) was proposed as a generic approach for automatic detection of 3D anatomical structures in many medical imaging modalities [1]. To accurately...
Yefeng Zheng, Bogdan Georgescu, Dorin Comaniciu
CVPR
2008
IEEE
16 years 7 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
ACL
2011
14 years 9 months ago
Learning Word Vectors for Sentiment Analysis
Unsupervised vector-based approaches to semantics can model rich lexical meanings, but they largely fail to capture sentiment information that is central to many word meanings and...
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Da...
NSDI
2008
15 years 7 months ago
Exploiting Machine Learning to Subvert Your Spam Filter
Using statistical machine learning for making security decisions introduces new vulnerabilities in large scale systems. This paper shows how an adversary can exploit statistical m...
Blaine Nelson, Marco Barreno, Fuching Jack Chi, An...
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IJCNN
2006
IEEE
15 years 11 months ago
A Variational EM Approach to Predicting Uncertainty in Supervised Learning
— In many applications of supervised learning, the conditional average of the target variables is not sufficient for prediction. The dependencies between the explanatory variabl...
Markus Harva