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JMLR
2010
102views more  JMLR 2010»
13 years 2 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...
NIPS
2007
13 years 9 months ago
Random Features for Large-Scale Kernel Machines
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
Ali Rahimi, Benjamin Recht
ICML
2004
IEEE
14 years 8 months ago
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
PRL
2008
198views more  PRL 2008»
13 years 7 months ago
Pose estimation and tracking using multivariate regression
This paper presents an extension of the relevance vector machine (RVM) algorithm to multivariate regression. This allows the application to the task of estimating the pose of an a...
Arasanathan Thayananthan, Ramanan Navaratnam, Bj&o...
GIS
2009
ACM
14 years 5 days ago
Machine learning approach to report prioritization with an application to travel time dissemination
This paper looks at the problem of data prioritization, commonly found in mobile ad-hoc networks. The proposed general solution uses a machine learning approach in order to learn ...
Piotr Szczurek, Bo Xu, Jie Lin, Ouri Wolfson