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» Learning Determinantal Point Processes
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AAAI
2012
11 years 9 months ago
Semi-Supervised Kernel Matching for Domain Adaptation
In this paper, we propose a semi-supervised kernel matching method to address domain adaptation problems where the source distribution substantially differs from the target distri...
Min Xiao, Yuhong Guo
ICIP
2007
IEEE
14 years 9 months ago
MuFeSaC: Learning When to Use Which Feature Detector
Interest point detectors are the starting point in image analysis for depth estimation using epipolar geometry and camera ego-motion estimation. With several detectors defined in ...
Sreenivas R. Sukumar, David L. Page, Hamparsum Boz...
PG
2003
IEEE
14 years 22 days ago
Neural Meshes: Statistical Learning Based on Normals
We present a method for the adaptive reconstruction of a surface directly from an unorganized point cloud. The algorithm is based on an incrementally expanding Neural Network and ...
Won-Ki Jeong, Ioannis P. Ivrissimtzis, Hans-Peter ...
CVPR
2008
IEEE
14 years 9 months ago
Spectral methods for semi-supervised manifold learning
Given a finite number of data points sampled from a low-dimensional manifold embedded in a high dimensional space together with the parameter vectors for a subset of the data poin...
Zhenyue Zhang, Hongyuan Zha, Min Zhang
CHI
2011
ACM
12 years 11 months ago
GreenHat: exploring the natural environment through experts' perspectives
We present GreenHat, an interactive mobile learning application that helps students learn about biodiversity and sustainability issues in their surroundings from experts’ points...
Kimiko Ryokai, Lora Oehlberg, Michael Manoochehri,...