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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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IWCLS
2007
Springer
15 years 4 months ago
A Principled Foundation for LCS
In this paper we explicitly identify the probabilistic model underlying LCS by linking it to a generalisation of the common Mixture-of-Experts model. Having an explicit representa...
Jan Drugowitsch, Alwyn Barry
PRL
2011
14 years 20 days ago
A Bayes-true data generator for evaluation of supervised and unsupervised learning methods
Benchmarking pattern recognition, machine learning and data mining methods commonly relies on real-world data sets. However, there are some disadvantages in using real-world data....
Janick V. Frasch, Aleksander Lodwich, Faisal Shafa...
CVPR
2005
IEEE
15 years 12 months ago
A Sparse Support Vector Machine Approach to Region-Based Image Categorization
Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multi...
Jinbo Bi, Yixin Chen, James Ze Wang
UAI
2001
14 years 11 months ago
Aggregating Learned Probabilistic Beliefs
We consider the task of aggregating beliefs of several experts. We assume that these beliefs are represented as probability distributions. We argue that the evaluation of any aggr...
Pedrito Maynard-Reid II, Urszula Chajewska
ALT
2003
Springer
15 years 6 months ago
Kernel Trick Embedded Gaussian Mixture Model
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...
Jingdong Wang, Jianguo Lee, Changshui Zhang