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» Framework for Agile Methods Classification
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CVPR
2009
IEEE
15 years 2 months ago
Robust Multi-Class Transductive Learning with Graphs
Graph-based methods form a main category of semisupervised learning, offering flexibility and easy implementation in many applications. However, the performance of these methods...
Wei Liu (Columbia University), Shih-fu Chang (Colu...
CHI
2010
ACM
14 years 2 months ago
Using concept maps to evaluate the usability of APIs
Application programming interfaces (APIs) are the interfaces to existing code structures, such as widgets, frameworks, or toolkits. Therefore, they very much do have an impact on ...
Jens Gerken, Hans-Christian Jetter, Harald Reitere...
ICDAR
2009
IEEE
14 years 2 months ago
Unsupervised Selection and Discriminative Estimation of Orthogonal Gaussian Mixture Models for Handwritten Digit Recognition
The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...
Xuefeng Chen, Xiabi Liu, Yunde Jia
SSPR
2004
Springer
14 years 25 days ago
An MCMC Feature Selection Technique for Characterizing and Classifying Spatial Region Data
We focus on characterizing spatial region data when distinct classes of structural patterns are present. We propose a novel statistical approach based on a supervised framework for...
Despina Kontos, Vasileios Megalooikonomou, Marc J....
ICIP
2007
IEEE
13 years 11 months ago
Unsupervised Nonlinear Manifold Learning
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...