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ICDM
2005
IEEE
163views Data Mining» more  ICDM 2005»
16 years 15 days ago
Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...
Thomas Takeo Osugi, Kun Deng, Stephen D. Scott
CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
16 years 13 days ago
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Chengcui Zhang, Xin Chen
ICML
2003
IEEE
16 years 4 days ago
The Significance of Temporal-Difference Learning in Self-Play Training TD-Rummy versus EVO-rummy
Reinforcement learning has been used for training game playing agents. The value function for a complex game must be approximated with a continuous function because the number of ...
Clifford Kotnik, Jugal K. Kalita
LOCA
2009
Springer
15 years 11 months ago
Activity Recognition from Sparsely Labeled Data Using Multi-Instance Learning
Abstract. Activity recognition has attracted increasing attention in recent years due to its potential to enable a number of compelling contextaware applications. As most approache...
Maja Stikic, Bernt Schiele
191
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CVPR
2010
IEEE
15 years 11 months ago
Learning Weights for Codebook in Image Classification
This paper presents a codebook learning approach for image classification and retrieval. It corresponds to learning a weighted similarity metric to satisfy that the weighted simil...
Hongping Cai, Krystian Mikolajczyk, Fei Yan