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» Learning Generative Models via Discriminative Approaches
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ICDAR
2009
IEEE
14 years 3 months ago
Fisher Kernels for Handwritten Word-spotting
The Fisher kernel is a generic framework which combines the benefits of generative and discriminative approaches to pattern classification. In this contribution, we propose to a...
Florent Perronnin, José A. Rodríguez...
ACL
2012
11 years 11 months ago
Labeling Documents with Timestamps: Learning from their Time Expressions
Temporal reasoners for document understanding typically assume that a document’s creation date is known. Algorithms to ground relative time expressions and order events often re...
Nathanael Chambers
COLING
2010
13 years 3 months ago
Unsupervised Discriminative Language Model Training for Machine Translation using Simulated Confusion Sets
An unsupervised discriminative training procedure is proposed for estimating a language model (LM) for machine translation (MT). An English-to-English synchronous context-free gra...
Zhifei Li, Ziyuan Wang, Sanjeev Khudanpur, Jason E...
ICIAR
2009
Springer
13 years 6 months ago
3D Human Pose Estimation from Static Images Using Local Features and Discriminative Learning
In this paper an approach to recover the 3D human body pose from static images is proposed. We adopt a discriminative learning technique to directly infer the 3D pose from appearan...
Suman Sedai, Farid Flitti, Mohammed Bennamoun, Du ...
ECML
2004
Springer
14 years 2 months ago
Fisher Kernels for Logical Sequences
One approach to improve the accuracy of classifications based on generative models is to combine them with successful discriminative algorithms. Fisher kernels were developed to c...
Kristian Kersting, Thomas Gärtner