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CVPR
2011
IEEE
15 years 3 months ago
Learning Message-Passing Inference Machines for Structured Prediction
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
Stephane Ross, Daniel Munoz, J. Andrew Bagnell
INTERSPEECH
2010
15 years 2 months ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang
JMLR
2010
230views more  JMLR 2010»
15 years 2 months ago
Learning Dissimilarities for Categorical Symbols
In this paper we learn a dissimilarity measure for categorical data, for effective classification of the data points. Each categorical feature (with values taken from a finite set...
Jierui Xie, Boleslaw K. Szymanski, Mohammed J. Zak...
ICCV
2011
IEEE
14 years 7 months ago
Discriminative Learning of Relaxed Hierarchy for Large-scale Visual Recognition
In the real visual world, the number of categories a classifier needs to discriminate is on the order of hundreds or thousands. For example, the SUN dataset [24] contains 899 sce...
Tianshi Gao, Daphne Koller
ISADS
1999
IEEE
15 years 12 months ago
Emergence of Communication for Negotiation by a Recurrent Neural Network
We believe that communication in multi-agent system has two major meanings. One of them is to transmit one agent's observed information to the other. The other meaning is to ...
Katsunari Shibata, Koji Ito