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» Bandit-Based Algorithms for Budgeted Learning
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PAKDD
2009
ACM
151views Data Mining» more  PAKDD 2009»
13 years 11 months ago
Budget Semi-supervised Learning
In this paper we propose to study budget semi-supervised learning, i.e., semi-supervised learning with a resource budget, such as a limited memory insufficient to accommodate and/...
Zhi-Hua Zhou, Michael Ng, Qiao-Qiao She, Yuan Jian...
ICML
2009
IEEE
14 years 5 months ago
A simpler unified analysis of budget perceptrons
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
Ilya Sutskever
NIPS
2008
13 years 6 months ago
Optimization on a Budget: A Reinforcement Learning Approach
Many popular optimization algorithms, like the Levenberg-Marquardt algorithm (LMA), use heuristic-based "controllers" that modulate the behavior of the optimizer during ...
Paul Ruvolo, Ian R. Fasel, Javier R. Movellan
ICML
2010
IEEE
13 years 6 months ago
Budgeted Nonparametric Learning from Data Streams
We consider the problem of extracting informative exemplars from a data stream. Examples of this problem include exemplarbased clustering and nonparametric inference such as Gauss...
Ryan Gomes, Andreas Krause
DA
2010
123views more  DA 2010»
13 years 1 months ago
Paradoxes in Learning and the Marginal Value of Information
We consider the Bayesian ranking and selection problem, in which one wishes to allocate an information collection budget as efficiently as possible to choose the best among severa...
Peter Frazier, Warren B. Powell