Sciweavers

1034 search results - page 18 / 207
» A Bayesian Metric for Evaluating Machine Learning Algorithms
Sort
View
CVPR
2006
IEEE
15 years 11 months ago
Meta-Evaluation of Image Segmentation Using Machine Learning
Image segmentation is a fundamental step in many computer vision applications. Generally, the choice of a segmentation algorithm, or parameterization of a given algorithm, is sele...
Hui Zhang, Sharath R. Cholleti, Sally A. Goldman, ...
JGO
2010
117views more  JGO 2010»
14 years 8 months ago
Machine learning problems from optimization perspective
Both optimization and learning play important roles in a system for intelligent tasks. On one hand, we introduce three types of optimization tasks studied in the machine learning l...
Lei Xu
ICML
2001
IEEE
15 years 10 months ago
Learning to Select Good Title Words: An New Approach based on Reverse Information Retrieval
In this paper, we show how we can learn to select good words for a document title. We view the problem of selecting good title words for a document as a variant of an Information ...
Rong Jin, Alexander G. Hauptmann
89
Voted
ICPR
2006
IEEE
15 years 10 months ago
On Kernel Selection in Relevance Vector Machines Using Stability Principle
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
Dmitry Kropotov, Nikita Ptashko, Oleg Vasiliev, Dm...
MCS
2000
Springer
15 years 1 months ago
Ensemble Methods in Machine Learning
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
Thomas G. Dietterich