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TNN
2008
178views more  TNN 2008»
15 years 1 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
SIGIR
2006
ACM
15 years 7 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 7 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 3 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
EMNLP
2009
14 years 11 months 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