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AAAI
2008
14 years 12 months ago
Manifold Integration with Markov Random Walks
Most manifold learning methods consider only one similarity matrix to induce a low-dimensional manifold embedded in data space. In practice, however, we often use multiple sensors...
Heeyoul Choi, Seungjin Choi, Yoonsuck Choe
CVPR
2003
IEEE
15 years 11 months ago
Learning Affinity Functions for Image Segmentation: Combining Patch-based and Gradient-based Approaches
This paper studies the problem of combining region and boundary cues for natural image segmentation. We employ a large database of manually segmented images in order to learn an o...
Charless Fowlkes, David R. Martin, Jitendra Malik
ICALT
2003
IEEE
15 years 2 months ago
Online Self-Assessment as a Learning Method
Algorithms and Programming Languages is a core subject in the BS Degree in Mathematics at the authors’ university. Some of the students are very interested in computer programmi...
Daniel Gayo-Avello, Hortensia Fernández-Cue...
UAI
1998
14 years 11 months ago
Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems
This paper presents two new approaches to decomposing and solving large Markov decision problems (MDPs), a partial decoupling method and a complete decoupling method. In these app...
Ronald Parr
UML
2005
Springer
15 years 3 months ago
Capturing Common and Variable Design Aspects for Ubiquitous Computing with MB-UID
Developing user interfaces for ubiquitous environments is a challenging task. In such an environment, users can apply different devices to accomplish the same or different tasks. ...
Alexander Boedcher, Kizito Mukasa, Detlef Zuelke