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» MultiK-MHKS: A Novel Multiple Kernel Learning Algorithm
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140
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CVPR
2012
IEEE
13 years 4 months ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
122
Voted
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 2 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 2 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
99
Voted
IPPS
2007
IEEE
15 years 8 months ago
Adaptive Predictor Integration for System Performance Prediction
The integration of multiple predictors promises higher prediction accuracy than the accuracy that can be obtained with a single predictor. The challenge is how to select the best ...
Jian Zhang, Renato J. O. Figueiredo
CVPR
2008
IEEE
16 years 3 months ago
Scene classification with low-dimensional semantic spaces and weak supervision
A novel approach to scene categorization is proposed. Similar to previous works of [11, 15, 3, 12], we introduce an intermediate space, based on a low dimensional semantic "t...
Nikhil Rasiwasia, Nuno Vasconcelos