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» Optimal Sequential Exploration: A Binary Learning Model
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IJCNN
2007
IEEE
14 years 1 months ago
On Extending the SMO Algorithm Sub-Problem
—The Support Vector Machine is a widely employed machine learning model due to its repeatedly demonstrated superior generalization performance. The Sequential Minimal Optimizatio...
Christopher Sentelle, Michael Georgiopoulos, Georg...
CORR
2010
Springer
171views Education» more  CORR 2010»
13 years 2 months ago
Online Learning in Opportunistic Spectrum Access: A Restless Bandit Approach
We consider an opportunistic spectrum access (OSA) problem where the time-varying condition of each channel (e.g., as a result of random fading or certain primary users' activ...
Cem Tekin, Mingyan Liu
ICPR
2008
IEEE
14 years 8 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
EUROCAST
2007
Springer
132views Hardware» more  EUROCAST 2007»
13 years 11 months ago
Using Omnidirectional BTS and Different Evolutionary Approaches to Solve the RND Problem
RND (Radio Network Design) is an important problem in mobile telecommunications (for example in mobile/cellular telephony), being also relevant in the rising area of sensor network...
Miguel A. Vega-Rodríguez, Juan Antonio G&oa...
JMLR
2010
125views more  JMLR 2010»
13 years 2 months ago
Regret Bounds for Gaussian Process Bandit Problems
Bandit algorithms are concerned with trading exploration with exploitation where a number of options are available but we can only learn their quality by experimenting with them. ...
Steffen Grünewälder, Jean-Yves Audibert,...