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CORR
2011
Springer
213views Education» more  CORR 2011»
14 years 4 months ago
Adapting to Non-stationarity with Growing Expert Ensembles
Forecasting sequences by expert ensembles generally assumes stationary or near-stationary processes; however, in complex systems and many real-world applications, we are frequentl...
Cosma Rohilla Shalizi, Abigail Z. Jacobs, Aaron Cl...
UAI
2003
14 years 11 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
KDD
2005
ACM
130views Data Mining» more  KDD 2005»
15 years 10 months ago
Simple and effective visual models for gene expression cancer diagnostics
In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...
ICPR
2004
IEEE
15 years 10 months ago
Probabilistic Combination of Multiple Modalities to Detect Interest
This paper describes a new approach to combine multiple modalities and applies it to the problem of affect recognition. The problem is posed as a combination of classifiers in a p...
Ashish Kapoor, Rosalind W. Picard, Yuri Ivanov
AAAI
2010
14 years 11 months ago
Collaborative Expert Portfolio Management
We consider the task of assigning experts from a portfolio of specialists in order to solve a set of tasks. We apply a Bayesian model which combines collaborative filtering with a...
David H. Stern, Horst Samulowitz, Ralf Herbrich, T...