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CRV
2009
IEEE
115views Robotics» more  CRV 2009»
15 years 8 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
16 years 2 months ago
On updates that constrain the features' connections during learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Jian Huang 0002
JCDL
2006
ACM
161views Education» more  JCDL 2006»
15 years 8 months ago
Learning metadata from the evidence in an on-line citation matching scheme
Citation matching, or the automatic grouping of bibliographic references that refer to the same document, is a data management problem faced by automatic digital libraries for sci...
Isaac G. Councill, Huajing Li, Ziming Zhuang, Sand...
ECCV
2008
Springer
16 years 3 months ago
SERBoost: Semi-supervised Boosting with Expectation Regularization
The application of semi-supervised learning algorithms to large scale vision problems suffers from the bad scaling behavior of most methods. Based on the Expectation Regularization...
Amir Saffari, Helmut Grabner, Horst Bischof
148
Voted
CORR
2011
Springer
198views Education» more  CORR 2011»
14 years 5 months ago
Decentralized Online Learning Algorithms for Opportunistic Spectrum Access
—The fundamental problem of multiple secondary users contending for opportunistic spectrum access over multiple channels in cognitive radio networks has been formulated recently ...
Yi Gai, Bhaskar Krishnamachari