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DIS
2009
Springer
15 years 9 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
128
Voted
ICML
2003
IEEE
16 years 3 months ago
Identifying Predictive Structures in Relational Data Using Multiple Instance Learning
This paper introduces an approach for identifying predictive structures in relational data using the multiple-instance framework. By a predictive structure, we mean a structure th...
Amy McGovern, David Jensen
123
Voted
ISVC
2010
Springer
15 years 28 days ago
Attention-Based Target Localization Using Multiple Instance Learning
Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic re...
Karthik Sankaranarayanan, James W. Davis
ICTAI
2003
IEEE
15 years 7 months ago
A Novel Bag Generator for Image Database Retrieval With Multi-Instance Learning Techniques
In multi-instance learning, the training examples are bags composed of instances without labels and the task is to predict the labels of unseen bags through analyzing the training...
Zhi-Hua Zhou, Min-Ling Zhang, Ke-Jia Chen
PAMI
2007
187views more  PAMI 2007»
15 years 1 months ago
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...