—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...
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...
—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...
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...
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...