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JMLR
2002
111views more  JMLR 2002»
15 years 6 months ago
The Learning-Curve Sampling Method Applied to Model-Based Clustering
We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computatio...
Christopher Meek, Bo Thiesson, David Heckerman
JMLR
2010
206views more  JMLR 2010»
15 years 1 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
IROS
2006
IEEE
127views Robotics» more  IROS 2006»
16 years 10 days ago
Learning Predictive Features in Affordance based Robotic Perception Systems
This work is about the relevance of Gibson’s concept of affordances [1] for visual perception in interactive and autonomous robotic systems. In extension to existing functional ...
Gerald Fritz, Lucas Paletta, Ralph Breithaupt, Eri...
AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
15 years 12 months ago
Learning to Fuse 3D+2D Based Face Recognition at Both Feature and Decision Levels
2D intensity images and 3D shape models are both useful for face recognition, but in different ways. While algorithms have long been developed using 2D or 3D data, recently has see...
Stan Z. Li, ChunShui Zhao, Meng Ao, Zhen Lei
BMCBI
2008
165views more  BMCBI 2008»
15 years 6 months ago
Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics
Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides...
Wiebke Timm, Alexandra Scherbart, Sebastian Bö...