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SSPR
2010
Springer
13 years 5 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
EMMCVPR
2009
Springer
14 years 1 months ago
Clustering-Based Construction of Hidden Markov Models for Generative Kernels
Generative kernels represent theoretically grounded tools able to increase the capabilities of generative classification through a discriminative setting. Fisher Kernel is the fi...
Manuele Bicego, Marco Cristani, Vittorio Murino, E...
ACMSE
2005
ACM
14 years 8 days ago
Investigating hidden Markov models capabilities in anomaly detection
Hidden Markov Model (HMM) based applications are common in various areas, but the incorporation of HMM's for anomaly detection is still in its infancy. This paper aims at cla...
Shrijit S. Joshi, Vir V. Phoha
COLING
2008
13 years 8 months ago
A Hybrid Generative/Discriminative Framework to Train a Semantic Parser from an Un-annotated Corpus
We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HMSV...
Deyu Zhou, Yulan He
ICDAR
2007
IEEE
14 years 1 months ago
Minimum Error Discriminative Training for Radical-Based Online Chinese Handwriting Recognition
Free style Chinese handwriting recognition continues to pose a challenge to researchers due to the variety of Chinese writing styles. To recognize handwritten characters in an onl...
Y. Zhang, P. Liu, F. Soong