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» Learning Generative Models with the Up-Propagation Algorithm
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89
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ECCV
2004
Springer
15 years 11 months ago
Recognition by Probabilistic Hypothesis Construction
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
Pierre Moreels, Michael Maire, Pietro Perona
KDD
2002
ACM
160views Data Mining» more  KDD 2002»
15 years 10 months ago
Scaling multi-class support vector machines using inter-class confusion
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
Shantanu Godbole, Sunita Sarawagi, Soumen Chakraba...
SIGIR
2011
ACM
14 years 14 days ago
Social context summarization
We study a novel problem of social context summarization for Web documents. Traditional summarization research has focused on extracting informative sentences from standard docume...
Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, J...
72
Voted
CORR
2010
Springer
146views Education» more  CORR 2010»
14 years 9 months ago
Active Learning for Hidden Attributes in Networks
In many networks, vertices have hidden attributes that are correlated with the network's topology. For instance, in social networks, people are more likely to be friends if t...
Xiaoran Yan, Yaojia Zhu, Jean-Baptiste Rouquier, C...
83
Voted
KDD
2007
ACM
167views Data Mining» more  KDD 2007»
15 years 10 months ago
Multiscale topic tomography
Modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. In this work, we propose a new probabilistic gr...
Ramesh Nallapati, Susan Ditmore, John D. Lafferty,...