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» PAC-Bayesian learning of linear classifiers
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CVPR
2012
IEEE
11 years 10 months ago
Understanding collective crowd behaviors: Learning a Mixture model of Dynamic pedestrian-Agents
In this paper, a new Mixture model of Dynamic pedestrian-Agents (MDA) is proposed to learn the collective behavior patterns of pedestrians in crowded scenes. Collective behaviors ...
Bolei Zhou, Xiaogang Wang, Xiaoou Tang
PR
2006
99views more  PR 2006»
13 years 7 months ago
Class-dependent PCA, MDC and LDA: A combined classifier for pattern classification
Several pattern classifiers give high classification accuracy but their storage requirements and processing time are severely expensive. On the other hand, some classifiers requir...
Alok Sharma, Kuldip K. Paliwal, Godfrey C. Onwubol...
AUSAI
2006
Springer
13 years 11 months ago
Voting Massive Collections of Bayesian Network Classifiers for Data Streams
Abstract. We present a new method for voting exponential (in the number of attributes) size sets of Bayesian classifiers in polynomial time with polynomial memory requirements. Tra...
Remco R. Bouckaert
EVOW
2008
Springer
13 years 9 months ago
A Hybrid Random Subspace Classifier Fusion Approach for Protein Mass Spectra Classification
Classifier fusion strategies have shown great potential to enhance the performance of pattern recognition systems. There is an agreement among researchers in classifier combination...
Amin Assareh, Mohammad Hassan Moradi, L. Gwenn Vol...
JAIR
2006
110views more  JAIR 2006»
13 years 7 months ago
Domain Adaptation for Statistical Classifiers
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Hal Daumé III, Daniel Marcu