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PAMI
2012
8 years 3 months ago
Quantifying and Transferring Contextual Information in Object Detection
— Context is critical for reducing the uncertainty in object detection. However, context modelling is challenging because there are often many different types of contextual infor...
Wei-Shi Zheng, Shaogang Gong, Tao Xiang
JMLR
2012
8 years 3 months ago
Factorized Asymptotic Bayesian Inference for Mixture Modeling
This paper proposes a novel Bayesian approximation inference method for mixture modeling. Our key idea is to factorize marginal log-likelihood using a variational distribution ove...
Ryohei Fujimaki, Satoshi Morinaga
EMNLP
2011
9 years 1 months ago
Random Walk Inference and Learning in A Large Scale Knowledge Base
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...
Ni Lao, Tom M. Mitchell, William W. Cohen
AAAI
2011
9 years 1 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
TIST
2011
136views more  TIST 2011»
9 years 8 months ago
Probabilistic models for concurrent chatting activity recognition
Recognition of chatting activities in social interactions is useful for constructing human social networks. However, the existence of multiple people involved in multiple dialogue...
Jane Yung-jen Hsu, Chia-chun Lian, Wan-rong Jih
CEC
2007
IEEE
10 years 7 months ago
A study on application of fitness inference method to PC-IGA
— This paper applies the fitness inference method to Interactive Genetic Algorithm based on Paired Comparison (PC-IGA). PC-IGA enables users to reduce the mental burden for eval...
Yoshinobu Watanabe, Tomohiro Yoshikawa, Takeshi Fu...
ICIG
2009
IEEE
10 years 8 months ago
Discriminative Maximum Margin Image Object Categorization with Exact Inference
Categorizing multiple objects in images is essentially a structured prediction problem: the label of an object is in general dependent on the labels of other objects in the image....
Qinfeng Shi, Luping Zhou, Li Cheng, Dale Schuurman...
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