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JMLR
2012
9 years 3 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
JGO
2011
89views more  JGO 2011»
10 years 4 months ago
Model building using bi-level optimization
Abstract In many problems from different disciplines such as engineering, physics, medicine, and biology, a series of experimental data is used in order to generate a model that ca...
Georges K. Saharidis, Ioannis P. Androulakis, Mari...
BMCBI
2011
10 years 5 months ago
To aggregate or not to aggregate high-dimensional classifiers
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
BMCBI
2008
101views more  BMCBI 2008»
11 years 1 months ago
Term-tissue specific models for prediction of gene ontology biological processes using transcriptional profiles of aging in dros
Background: Predictive classification on the base of gene expression profiles appeared recently as an attractive strategy for identifying the biological functions of genes. Gene O...
Wensheng Zhang, Sige Zou, Jiuzhou Song
SDM
2008
SIAM
165views Data Mining» more  SDM 2008»
11 years 2 months ago
On the Dangers of Cross-Validation. An Experimental Evaluation
Cross validation allows models to be tested using the full training set by means of repeated resampling; thus, maximizing the total number of points used for testing and potential...
R. Bharat Rao, Glenn Fung
ICML
1994
IEEE
11 years 4 months ago
Efficient Algorithms for Minimizing Cross Validation Error
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
Andrew W. Moore, Mary S. Lee
COLT
1995
Springer
11 years 4 months ago
Regression NSS: An Alternative to Cross Validation
The Noise Sensitivity Signature (NSS), originally introduced by Grossman and Lapedes (1993), was proposed as an alternative to cross validation for selecting network complexity. I...
Michael P. Perrone, Brian S. Blais
IJCNN
2006
IEEE
11 years 7 months ago
Model Selection via Bilevel Optimization
— A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be sel...
Kristin P. Bennett, Jing Hu, Xiaoyun Ji, Gautam Ku...
ICASSP
2009
IEEE
11 years 8 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
KDD
2007
ACM
142views Data Mining» more  KDD 2007»
12 years 1 months ago
Towards Privacy-Preserving Model Selection
Abstract. Model selection is an important problem in statistics, machine learning, and data mining. In this paper, we investigate the problem of enabling multiple parties to perfor...
Zhiqiang Yang, Sheng Zhong, Rebecca N. Wright
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