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» A Framework for Multiple-Instance Learning
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134
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ICDAR
2009
IEEE
15 years 10 months ago
Learning and Adaptation for Improving Handwritten Character Recognizers
Writer independent handwriting recognition systems are limited in their accuracy, primarily due the large variations in writing styles of most characters. Samples from a single ch...
Naveen Chandra Tewari, Anoop M. Namboodiri
134
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ICDM
2007
IEEE
150views Data Mining» more  ICDM 2007»
15 years 10 months ago
Connections between Mining Frequent Itemsets and Learning Generative Models
Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...
123
Voted
WECWIS
2003
IEEE
120views ECommerce» more  WECWIS 2003»
15 years 9 months ago
Reinforcement Learning Applications in Dynamic Pricing of Retail Markets
In this paper, we investigate the use of reinforcement learning (RL) techniques to the problem of determining dynamic prices in an electronic retail market. As representative mode...
C. V. L. Raju, Y. Narahari, K. Ravikumar
203
Voted
CVPR
2011
IEEE
14 years 11 months ago
Learning Context for Collective Activity Recognition
In this paper we present a framework for the recognition of collective human activities. A collective activity is defined or reinforced by the existence of coherent behavior of i...
Wongun Choi, Silvio Savarese, Khuram Shahid
167
Voted
TKDE
2011
479views more  TKDE 2011»
14 years 10 months ago
Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
Wei Zhang, Zhouchen Lin, Xiaoou Tang