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DAGM
2005
Springer
14 years 2 months ago
Agglomerative Grouping of Observations by Bounding Entropy Variation
Abstract. An information theoretic framework for grouping observations is proposed. The entropy change incurred by new observations is analyzed using the Kalman filter update equa...
Christian Beder
KDD
2001
ACM
149views Data Mining» more  KDD 2001»
14 years 9 months ago
Maximum entropy methods for biological sequence modeling
Many of the same modeling methods used in natural languages, speci cally Markov models and HMM's, have also been applied to biological sequence analysis. In recent years, nat...
Eugen C. Buehler, Lyle H. Ungar
AI
1998
Springer
13 years 8 months ago
Uncertainty Measures of Rough Set Prediction
The main statistics used in rough set data analysis, the approximation quality, is of limited value when there is a choice of competing models for predicting a decision variable. ...
Ivo Düntsch, Günther Gediga
ICML
2009
IEEE
14 years 9 months ago
MedLDA: maximum margin supervised topic models for regression and classification
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
Jun Zhu, Amr Ahmed, Eric P. Xing
ICA
2004
Springer
14 years 2 months ago
Minimax Mutual Information Approach for ICA of Complex-Valued Linear Mixtures
Abstract. Recently, the authors developed the Minimax Mutual Information algorithm for linear ICA of real-valued mixtures, which is based on a density estimate stemming from Jaynes...
Jian-Wu Xu, Deniz Erdogmus, Yadunandana N. Rao, Jo...