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» Experimental perspectives on learning from imbalanced data
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MICCAI
2007
Springer
14 years 1 months ago
Robust Autonomous Model Learning from 2D and 3D Data Sets
In this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle. From a set of training images or volu...
Georg Langs, Rene Donner, Philipp Peloschek, Horst...
CIKM
1997
Springer
13 years 12 months ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
CVPR
2012
IEEE
11 years 10 months ago
Large scale metric learning from equivalence constraints
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Martin Köstinger, Martin Hirzer, Paul Wohlhar...
TCBB
2011
13 years 2 months ago
Learning Genetic Regulatory Network Connectivity from Time Series Data
Recent experimental advances facilitate the collection of time series data that indicate which genes in a cell are expressed. This paper proposes an efficient method to generate th...
Nathan A. Barker, Chris J. Myers, Hiroyuki Kuwahar...
CVPR
2012
IEEE
11 years 10 months ago
Geometry constrained sparse coding for single image super-resolution
The choice of the over-complete dictionary that sparsely represents data is of prime importance for sparse codingbased image super-resolution. Sparse coding is a typical unsupervi...
Xiaoqiang Lu, Haoliang Yuan, Pingkun Yan, Yuan Yua...