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» Active Learning with Model Selection in Linear Regression
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CVPR
2011
IEEE
13 years 4 months ago
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
Sudheendra Vijayanarasimhan, Kristen Grauman
ML
2002
ACM
135views Machine Learning» more  ML 2002»
13 years 8 months ago
Bayesian Treed Models
When simple parametric models such as linear regression fail to adequately approximate a relationship across an entire set of data, an alternative may be to consider a partition o...
Hugh A. Chipman, Edward I. George, Robert E. McCul...
IWANN
2005
Springer
14 years 2 months ago
Load Forecasting Using Fixed-Size Least Squares Support Vector Machines
Based on the Nystr¨om approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large sc...
Marcelo Espinoza, Johan A. K. Suykens, Bart De Moo...
ISCC
2006
IEEE
188views Communications» more  ISCC 2006»
14 years 2 months ago
Active Learning Driven Data Acquisition for Sensor Networks
Online monitoring of a physical phenomenon over a geographical area is a popular application of sensor networks. Networks representative of this class of applications are typicall...
Anish Muttreja, Anand Raghunathan, Srivaths Ravi, ...
INTERSPEECH
2010
13 years 3 months ago
HMM adaptation using linear spline interpolation with integrated spline parameter training for robust speech recognition
We recently proposed a method for HMM adaptation to noisy environments called Linear Spline Interpolation (LSI). LSI uses linear spline regression to model the relationship betwee...
Michael L. Seltzer, Alex Acero