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ICCV
2011
IEEE
14 years 6 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
ECML
2001
Springer
15 years 11 months ago
A Framework for Learning Rules from Multiple Instance Data
Abstract. This paper proposes a generic extension to propositional rule learners to handle multiple-instance data. In a multiple-instance representation, each learning example is r...
Yann Chevaleyre, Jean-Daniel Zucker
NIPS
2000
15 years 8 months ago
Kernel Expansions with Unlabeled Examples
Modern classification applications necessitate supplementing the few available labeled examples with unlabeled examples to improve classification performance. We present a new tra...
Martin Szummer, Tommi Jaakkola
ICASSP
2011
IEEE
14 years 10 months ago
Improvement to esprit-type frequency estimators via reducing data redundancy
In this paper, the problem of estimating the damping factor and frequency parameters from multiple cisoids in noise is addressed. We rst propose a data matrix which generalizes th...
Weize Sun, Hing Cheung So
WWW
2009
ACM
16 years 7 months ago
Smart Miner: a new framework for mining large scale web usage data
In this paper, we propose a novel framework called SmartMiner for web usage mining problem which uses link information for producing accurate user sessions and frequent navigation...
Murat Ali Bayir, Ismail Hakki Toroslu, Ahmet Cosar...