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ICML
2004
IEEE
16 years 7 months ago
Learning Bayesian network classifiers by maximizing conditional likelihood
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
Daniel Grossman, Pedro Domingos
ALT
2007
Springer
16 years 3 months ago
Learning Rational Stochastic Tree Languages
Abstract. We consider the problem of learning stochastic tree languages, i.e. probability distributions over a set of trees T(F), from a sample of trees independently drawn accordi...
François Denis, Amaury Habrard
ICPR
2008
IEEE
16 years 2 months ago
Online Feature Evaluation For Object Tracking Using Kalman Filter
An online feature evaluation method for visual object tracking is put forward in this paper. Firstly, a combined feature set is built using color histogram (HC) bins and gradien...
Zhenjun Han, Qixiang Ye, Jianbin Jiao+
ICC
2009
IEEE
114views Communications» more  ICC 2009»
16 years 1 months ago
Markov Chain Minimum Bit Error Rate Detection for Multi-Functional MIMO Uplink
— In this paper, we introduce a novel Markov Chain (MC) representation aided Minimum Bit Error Rate (MBER) detection method that is applicable to an M-QAM modulated SDM/SDMA upli...
Shinya Sugiura, Sheng Chen, Lajos Hanzo
WIAMIS
2009
IEEE
16 years 1 months ago
Towards fully un-supervised methods for generating object detection classifiers using social data
In this work a framework for constructing object detection classifiers using weakly annotated social data is proposed. Social information is combined with computer vision techniq...
Spiros Nikolopoulos, Elisavet Chatzilari, Eirini G...