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TKDE
2010
168views more  TKDE 2010»
14 years 8 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
IJON
2010
119views more  IJON 2010»
14 years 8 months ago
Hyperparameter learning in probabilistic prototype-based models
We present two approaches to extend Robust Soft Learning Vector Quantization (RSLVQ). This algorithm for nearest prototype classification is derived from an explicit cost functio...
Petra Schneider, Michael Biehl, Barbara Hammer
TVCG
2012
213views Hardware» more  TVCG 2012»
13 years 11 days ago
Mesh-Driven Vector Field Clustering and Visualization: An Image-Based Approach
—Vector field visualization techniques have evolved very rapidly over the last two decades, however, visualizing vector fields on complex boundary surfaces from computational ...
Zhenmin Peng, Edward Grundy, Robert S. Laramee, Gu...
APVIS
2009
14 years 11 months ago
Visualizing time-varying features with TAC-based distance fields
To analyze time-varying data sets, tracking features over time is often necessary to better understand the dynamic nature of the underlying physical process. Tracking 3D time-vary...
Teng-Yok Lee, Han-Wei Shen
ICML
2005
IEEE
15 years 10 months ago
Supervised clustering with support vector machines
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...
Thomas Finley, Thorsten Joachims