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» Shape Priors using Manifold Learning Techniques
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AAAI
2010
15 years 5 months ago
G-Optimal Design with Laplacian Regularization
In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, L...
ICPR
2006
IEEE
16 years 5 months ago
Learning Pairwise Similarity for Data Clustering
Each clustering algorithm induces a similarity between given data points, according to the underlying clustering criteria. Given the large number of available clustering technique...
Ana L. N. Fred, Anil K. Jain
146
Voted
SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
15 years 5 months ago
Making Time-Series Classification More Accurate Using Learned Constraints
It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
KDD
2010
ACM
242views Data Mining» more  KDD 2010»
15 years 6 months ago
A scalable two-stage approach for a class of dimensionality reduction techniques
Dimensionality reduction plays an important role in many data mining applications involving high-dimensional data. Many existing dimensionality reduction techniques can be formula...
Liang Sun, Betul Ceran, Jieping Ye
HRI
2006
ACM
15 years 10 months ago
Teaching robots by moulding behavior and scaffolding the environment
Programming robots to carry out useful tasks is both a complex and non-trivial exercise. A simple and intuitive method to allow humans to train and shape robot behaviour is clearl...
Joe Saunders, Chrystopher L. Nehaniv, Kerstin Daut...