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» Large Margin Classification Using the Perceptron Algorithm
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CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
15 years 4 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
142
Voted
SIGMETRICS
2011
ACM
191views Hardware» more  SIGMETRICS 2011»
14 years 5 months ago
Stability analysis of QCN: the averaging principle
Data Center Networks have recently caused much excitement in the industry and in the research community. They represent the convergence of networking, storage, computing and virtu...
Mohammad Alizadeh, Abdul Kabbani, Berk Atikoglu, B...
100
Voted
ICML
2007
IEEE
16 years 3 months ago
On learning linear ranking functions for beam search
Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
Yuehua Xu, Alan Fern
123
Voted
PAKDD
2000
ACM
140views Data Mining» more  PAKDD 2000»
15 years 5 months ago
Performance Controlled Data Reduction for Knowledge Discovery in Distributed Databases
The objective of data reduction is to obtain a compact representation of a large data set to facilitate repeated use of non-redundant information with complex and slow learning alg...
Slobodan Vucetic, Zoran Obradovic
116
Voted
SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
15 years 11 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