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» Learning Generative Models via Discriminative Approaches
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EMNLP
2004
13 years 10 months ago
Comparing and Combining Generative and Posterior Probability Models: Some Advances in Sentence Boundary Detection in Speech
We compare and contrast two different models for detecting sentence-like units in continuous speech. The first approach uses hidden Markov sequence models based on N-grams and max...
Yang Liu, Andreas Stolcke, Elizabeth Shriberg, Mar...
NIPS
2003
13 years 10 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Stuart Andrews, Thomas Hofmann
DAGM
2010
Springer
13 years 10 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen
NAACL
2004
13 years 10 months ago
Robust Reading: Identification and Tracing of Ambiguous Names
A given entity, representing a person, a location or an organization, may be mentioned in text in multiple, ambiguous ways. Understanding natural language requires identifying whe...
Xin Li, Paul Morie, Dan Roth
CVPR
2008
IEEE
14 years 11 months ago
Large margin pursuit for a Conic Section classifier
Learning a discriminant becomes substantially more difficult when the datasets are high-dimensional and the available samples are few. This is often the case in computer vision an...
Santhosh Kodipaka, Arunava Banerjee, Baba C. Vemur...