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PR
2011
14 years 10 months ago
A variational Bayesian methodology for hidden Markov models utilizing Student's-t mixtures
The Student’s-t hidden Markov model (SHMM) has been recently proposed as a robust to outliers form of conventional continuous density hidden Markov models, trained by means of t...
Sotirios Chatzis, Dimitrios I. Kosmopoulos
NN
2010
Springer
189views Neural Networks» more  NN 2010»
14 years 10 months ago
Sparse kernel learning with LASSO and Bayesian inference algorithm
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Junbin Gao, Paul W. Kwan, Daming Shi
108
Voted
EMNLP
2006
15 years 4 months ago
Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation Pipelines
The end-to-end performance of natural language processing systems for compound tasks, such as question answering and textual entailment, is often hampered by use of a greedy 1-bes...
Jenny Rose Finkel, Christopher D. Manning, Andrew ...
NC
1998
102views Neural Networks» more  NC 1998»
15 years 4 months ago
Outliers and Bayesian Inference
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
Peter Sykacek
ML
1998
ACM
153views Machine Learning» more  ML 1998»
15 years 2 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun