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» MILIS: Multiple Instance Learning with Instance Selection
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DGO
2008
126views Education» more  DGO 2008»
13 years 9 months ago
Active learning for e-rulemaking: public comment categorization
We address the e-rulemaking problem of reducing the manual labor required to analyze public comment sets. In current and previous work, for example, text categorization techniques...
Stephen Purpura, Claire Cardie, Jesse Simons
IJCV
2008
106views more  IJCV 2008»
13 years 7 months ago
Evaluation of Localized Semantics: Data, Methodology, and Experiments
We present a new data set encoding localized semantics for 1014 images and a methodology for using this kind of data for recognition evaluation. This methodology establishes protoc...
Kobus Barnard, Quanfu Fan, Ranjini Swaminathan, An...
GLVLSI
2005
IEEE
133views VLSI» more  GLVLSI 2005»
14 years 1 months ago
Generating decision regions in analog measurement spaces
We develop a neural network that learns to separate the nominal from the faulty instances of a circuit in a measurement space. We demonstrate that the required separation boundari...
Haralampos-G. D. Stratigopoulos, Yiorgos Makris
PKDD
2001
Springer
120views Data Mining» more  PKDD 2001»
14 years 1 days ago
Distinguishing Natural Language Processes on the Basis of fMRI-Measured Brain Activation
We present a method for distinguishing two subtly different mental states, on the basis of the underlying brain activation measured with fMRI. The method uses a classifier to lea...
Francisco Pereira, Marcel Just, Tom M. Mitchell
AAAI
2006
13 years 9 months ago
Thresholding for Making Classifiers Cost-sensitive
In this paper we propose a very simple, yet general and effective method to make any cost-insensitive classifiers (that can produce probability estimates) cost-sensitive. The meth...
Victor S. Sheng, Charles X. Ling