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PR
2008
144views more  PR 2008»
15 years 4 months ago
Kernel quadratic discriminant analysis for small sample size problem
It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...
Jie Wang, Konstantinos N. Plataniotis, Juwei Lu, A...
147
Voted
AGI
2011
14 years 8 months ago
Comparing Humans and AI Agents
Comparing humans and machines is one important source of information about both machine and human strengths and limitations. Most of these comparisons and competitions are performe...
Javier Insa-Cabrera, David L. Dowe, Sergio Espa&nt...
WWW
2010
ACM
15 years 11 months ago
Factorizing personalized Markov chains for next-basket recommendation
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn...
Steffen Rendle, Christoph Freudenthaler, Lars Schm...
TSMC
2008
164views more  TSMC 2008»
15 years 4 months ago
Bagging and Boosting Negatively Correlated Neural Networks
In this paper, we propose two cooperative ensemble learning algorithms, i.e., NegBagg and NegBoost, for designing neural network (NN) ensembles. The proposed algorithms incremental...
Md. Monirul Islam, Xin Yao, S. M. Shahriar Nirjon,...
141
Voted
NOSSDAV
2009
Springer
15 years 11 months ago
SLIPstream: scalable low-latency interactive perception on streaming data
A critical problem in implementing interactive perception applications is the considerable computational cost of current computer vision and machine learning algorithms, which typ...
Padmanabhan Pillai, Lily B. Mummert, Steven W. Sch...