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» Bandit-Based Algorithms for Budgeted Learning
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SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
14 years 4 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic
CVPR
2010
IEEE
14 years 3 months ago
Far-Sighted Active Learning on a Budget for Image and Video Recognition
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Sudheendra Vijayanarasimhan, Prateek Jain, Kristen...
SIAMCOMP
2008
140views more  SIAMCOMP 2008»
13 years 7 months ago
The Forgetron: A Kernel-Based Perceptron on a Budget
Abstract. The Perceptron algorithm, despite its simplicity, often performs well in online classification tasks. The Perceptron becomes especially effective when it is used in conju...
Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
COLT
2004
Springer
13 years 11 months ago
The Budgeted Multi-armed Bandit Problem
straction of the following scenarios: choosing from among a set of alternative treatments after a fixed number of clinical trials, determining the best parameter settings for a pro...
Omid Madani, Daniel J. Lizotte, Russell Greiner
KDD
2005
ACM
106views Data Mining» more  KDD 2005»
14 years 26 days ago
Enhancing the lift under budget constraints: an application in the mutual fund industry
A lift curve, with the true positive rate on the y-axis and the customer pull (or contact) rate on the x-axis, is often used to depict the model performance in many data mining ap...
Lian Yan, Michael Fassino, Patrick Baldasare