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TNN
2008
178views more  TNN 2008»
15 years 2 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
104
Voted
SIGIR
2006
ACM
15 years 8 months ago
Learning a ranking from pairwise preferences
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
Ben Carterette, Desislava Petkova
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
15 years 8 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
ICIP
2007
IEEE
16 years 4 months ago
Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
Tomas Izo, W. Eric L. Grimson
105
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EMNLP
2009
15 years 12 days ago
Supervised Models for Coreference Resolution
Traditional learning-based coreference resolvers operate by training a mentionpair classifier for determining whether two mentions are coreferent or not. Two independent lines of ...
Md. Altaf ur Rahman, Vincent Ng