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AAAI
2008
15 years 9 months ago
Maximum Entropy Inverse Reinforcement Learning
Recent research has shown the benefit of framing problems of imitation learning as solutions to Markov Decision Problems. This approach reduces learning to the problem of recoveri...
Brian Ziebart, Andrew L. Maas, J. Andrew Bagnell, ...
CVPR
2012
IEEE
13 years 9 months ago
The use of on-line co-training to reduce the training set size in pattern recognition methods: Application to left ventricle seg
The use of statistical pattern recognition models to segment the left ventricle of the heart in ultrasound images has gained substantial attention over the last few years. The mai...
Gustavo Carneiro, Jacinto C. Nascimento
ML
2000
ACM
149views Machine Learning» more  ML 2000»
15 years 6 months ago
BoosTexter: A Boosting-based System for Text Categorization
This work focuses on algorithms which learn from examples to perform multiclass text and speech categorization tasks. Our approach is based on a new and improved family of boosting...
Robert E. Schapire, Yoram Singer
ICASSP
2009
IEEE
16 years 1 months ago
Maximizing global entropy reduction for active learning in speech recognition
We propose a new active learning algorithm to address the problem of selecting a limited subset of utterances for transcribing from a large amount of unlabeled utterances so that ...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
ICMCS
2007
IEEE
155views Multimedia» more  ICMCS 2007»
16 years 1 months ago
Hidden Maximum Entropy Approach for Visual Concept Modeling
Recently, the bag-of-words approach has been successfully applied to automatic image annotation, object recognition, etc. The method needs to first quantize an image using the vis...
Sheng Gao, Joo-Hwee Lim, Qibin Sun