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ML
2012
ACM
388views Machine Learning» more  ML 2012»
13 years 9 months ago
Statistical analysis of kernel-based least-squares density-ratio estimation
The ratio of two probability densities can be used for solving various machine learning tasks such as covariate shift adaptation (importance sampling), outlier detection (likeliho...
Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama
EMMCVPR
1999
Springer
15 years 6 months ago
On Fitting Mixture Models
Consider the problem of tting a nite Gaussian mixture, with an unknown number of components, to observed data. This paper proposes a new minimum description length (MDL) type crite...
Mário A. T. Figueiredo, José M. N. L...
EVOW
2004
Springer
15 years 7 months ago
Analysis of Proteomic Pattern Data for Cancer Detection
Abstract. In this paper we analyze two proteomic pattern datasets containing measurements from ovarian and prostate cancer samples. In particular, a linear and a quadratic support ...
Kees Jong, Elena Marchiori, Aad van der Vaart
123
Voted
TMI
2010
206views more  TMI 2010»
14 years 8 months ago
Random Subspace Ensembles for fMRI Classification
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
Ludmila I. Kuncheva, Juan José Rodrí...
136
Voted
CDC
2008
IEEE
126views Control Systems» more  CDC 2008»
15 years 3 months ago
Subspace identification using predictor estimation via Gaussian regression
In this paper we propose a new nonparametric approach to identification of linear time invariant systems using subspace methods. The nonparametric paradigm to prediction of station...
Alessandro Chiuso, Gianluigi Pillonetto, Giuseppe ...