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98
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DIS
2009
Springer
15 years 7 months ago
MICCLLR: Multiple-Instance Learning Using Class Conditional Log Likelihood Ratio
Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
Yasser El-Manzalawy, Vasant Honavar
96
Voted
PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
15 years 7 months ago
Mining Graph Evolution Rules
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
Michele Berlingerio, Francesco Bonchi, Björn ...
ICASSP
2008
IEEE
15 years 7 months ago
An information theoretic approach to processing management
In region surveillance applications, sensors oftentimes accumulate an overwhelmingly large amount of data, making it infeasible to process all of the collected data in real-time. ...
Christopher M. Kreucher, Kevin M. Carter
120
Voted
ICASSP
2008
IEEE
15 years 7 months ago
Transmit codes and receive filters for pulse compression radar systems
Pulse compression radar systems make use of transmit code sequences and receive filters that are specially designed to achieve good range resolution and target detection capabili...
Petre Stoica, Jian Li, Ming Xue
CVPR
2007
IEEE
15 years 7 months ago
Learning Generative Models via Discriminative Approaches
Generative model learning is one of the key problems in machine learning and computer vision. Currently the use of generative models is limited due to the difficulty in effective...
Zhuowen Tu
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