Sciweavers

Share
JMLR
2010
118views more  JMLR 2010»
8 years 6 months ago
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...
Gavin C. Cawley, Nicola L. C. Talbot
PAMI
2010
192views more  PAMI 2010»
8 years 10 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens
BMEI
2009
IEEE
9 years 1 months ago
A Kurtosis and Skewness Based Criterion for Model Selection on Gaussian Mixture
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
Lin Wang, Jinwen Ma
IJCNN
2000
IEEE
9 years 4 months ago
Continuous Optimization of Hyper-Parameters
Many machine learning algorithms can be formulated as the minimization of a training criterion which involves (1) \training errors" on each training example and (2) some hype...
Yoshua Bengio
PKDD
2007
Springer
121views Data Mining» more  PKDD 2007»
9 years 6 months ago
Improved Algorithms for Univariate Discretization of Continuous Features
In discretization of a continuous variable its numerical value range is divided into a few intervals that are used in classification. For example, Na¨ıve Bayes can benefit from...
Jussi Kujala, Tapio Elomaa
AINA
2009
IEEE
9 years 7 months ago
Modeling Web Request and Session Level Arrivals
This paper is focused on modeling Web request and session level arrival processes. We propose a statistically rigorous approach which includes testing for non-stationarity and Gau...
Xuan Wang, Katerina Goseva-Popstojanova
ICML
2009
IEEE
10 years 27 days ago
Optimized expected information gain for nonlinear dynamical systems
This paper addresses the problem of active model selection for nonlinear dynamical systems. We propose a novel learning approach that selects the most informative subset of time-d...
Alberto Giovanni Busetto, Cheng Soon Ong, Joachim ...
ICPR
2000
IEEE
10 years 1 months ago
Unsupervised Selection and Estimation of Finite Mixture Models
We propose a new method for fitting mixture models that performs component selection and does not require external initialization. The novelty of our approach includes: a minimum ...
Anil K. Jain, Mário A. T. Figueiredo
ECCV
2006
Springer
10 years 2 months ago
Density Estimation Using Mixtures of Mixtures of Gaussians
In this paper we present a new density estimation algorithm using mixtures of mixtures of Gaussians. The new algorithm overcomes the limitations of the popular Expectation Maximiza...
Wael Abd-Almageed, Larry S. Davis
CVPR
2004
IEEE
10 years 2 months ago
Minimum Effective Dimension for Mixtures of Subspaces: A Robust GPCA Algorithm and Its Applications
In this paper, we propose a robust model selection criterion for mixtures of subspaces called minimum effective dimension (MED). Previous information-theoretic model selection cri...
Kun Huang, René Vidal, Yi Ma
books