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IWANN
2007
Springer
15 years 3 months ago
Non-parametric Residual Variance Estimation in Supervised Learning
The residual variance estimation problem is well-known in statistics and machine learning with many applications for example in the field of nonlinear modelling. In this paper, we...
Elia Liitiäinen, Amaury Lendasse, Francesco C...
JMLR
2010
102views more  JMLR 2010»
14 years 4 months ago
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels
Estimating the error rates of classifiers or regression models is a fundamental task in machine learning which has thus far been studied exclusively using supervised learning tech...
Pinar Donmez, Guy Lebanon, Krishnakumar Balasubram...
ICML
2009
IEEE
15 years 4 months ago
Supervised learning from multiple experts: whom to trust when everyone lies a bit
We describe a probabilistic approach for supervised learning when we have multiple experts/annotators providing (possibly noisy) labels but no absolute gold standard. The proposed...
Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Anna K...
ECCV
2006
Springer
15 years 11 months ago
Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...
David J. Crandall, Daniel P. Huttenlocher
ICML
2007
IEEE
15 years 10 months ago
Spectral feature selection for supervised and unsupervised learning
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
Zheng Zhao, Huan Liu