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AAAI
2008
13 years 9 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
14 years 9 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
14 years 23 days 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
13 years 8 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
14 years 29 days 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