A Practical Approach to Feature Selection
ML '92 Proceedings of the Ninth International Workshop on Machine Learning
On the influence of the kernel on the consistency of support vector machines
The Journal of Machine Learning Research
An introduction to variable and feature selection
The Journal of Machine Learning Research
Use of the zero norm with linear models and kernel methods
The Journal of Machine Learning Research
Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
The Journal of Machine Learning Research
Combined SVM-Based Feature Selection and Classification
Machine Learning
Measuring statistical dependence with hilbert-schmidt norms
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Learning subspace kernels for classification
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
A Hilbert Space Embedding for Distributions
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
Microarray Design Using the Hilbert---Schmidt Independence Criterion
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
More generality in efficient multiple kernel learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Non-monotonic feature selection
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Consensus group stable feature selection
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Steganalysis by subtractive pixel adjacency matrix
Proceedings of the 11th ACM workshop on Multimedia and security
Semi-supervised Discriminant Analysis Based on Dependence Estimation
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Multi-label dimensionality reduction via dependence maximization
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Density Ratio Estimation: A New Versatile Tool for Machine Learning
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
A Least-squares Approach to Direct Importance Estimation
The Journal of Machine Learning Research
Supervised feature extraction using Hilbert-Schmidt norms
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Feature selection for support vector regression using probabilistic prediction
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Multilabel dimensionality reduction via dependence maximization
ACM Transactions on Knowledge Discovery from Data (TKDD)
Feature Selection by Approximating the Markov Blanket in a Kernel-Induced Space
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Discriminative semi-supervised feature selection via manifold regularization
IEEE Transactions on Neural Networks
Orientation distance-based discriminative feature extraction for multi-class classification
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
A General Framework for Analyzing Data from Two Short Time-Series Microarray Experiments
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Novel method for feature-set ranking applied to physical activity recognition
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Anomaly detection techniques for a web defacement monitoring service
Expert Systems with Applications: An International Journal
Linear discriminant dimensionality reduction
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
Feature subset selection with cumulate conditional mutual information minimization
Expert Systems with Applications: An International Journal
Feature selection via dependence maximization
The Journal of Machine Learning Research
Harmony-based feature selection to improve the nearest neighbor classification
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
Massively parallel feature selection: an approach based on variance preservation
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
A local information-based feature-selection algorithm for data regression
Pattern Recognition
Fuzzy rough based regularization in Generalized Multiple Kernel Learning
Computers & Mathematics with Applications
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We introduce a framework for filtering features that employs the Hilbert-Schmidt Independence Criterion (HSIC) as a measure of dependence between the features and the labels. The key idea is that good features should maximise such dependence. Feature selection for various supervised learning problems (including classification and regression) is unified under this framework, and the solutions can be approximated using a backward-elimination algorithm. We demonstrate the usefulness of our method on both artificial and real world datasets.