#### About

The workshop examines and invites discussion on a range of methods that have been developed for dimension reduction and feature selection. This is a core topic which has been addressed theoretically in many guises from the perspectives of boosting, eigenanalysis, optimisation, latent structure analysis, bayesian methods and traditional statistical approaches to name a few. As an applied technique many algorithms exist for feature selection and all real-world applications of machine learning include some aspect of this in their implementation.

In line with the Thematic Programme 'Linking Learning and Statistics with Optimisation' the workshop focuses on the integration between for example the statistical (frequentist and Bayesian) aspects as well as optimisation issues raised by subspace identification. We feel the workshop provides a real opportunity for interaction between different areas of research and its focus on a strongly applicable family of methods will promote active discussion between different areas of the research community.

Topics considered and contributions are sought in the following areas:

```
* Dimension reduction techniques, subspace methods
* Random projection methods
* Boosting
* Statistical analysis methods
* Bayesian approaches to feature selection
* Latent structure analysis/Probabilistic LSA
* Optimisation methods
* Novel applications of feature selection algorithms
* Open problems in the domain
```

More information can be found here.

#### Related categories

## Uploaded videos:

## Lectures

### Latent Semantic Variable Models

Feb 25, 2007

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29745 Views

### Some aspects of Latent Structure Analysis

Feb 25, 2007

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8121 Views

### Discrete PCA

Feb 25, 2007

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7193 Views

### In search of Non-Gaussian Components of a High-Dimensional Distribution

Feb 25, 2007

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4499 Views

### Auxillary Variational Information Maximization for Dimensionality Reduction

Feb 25, 2007

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4636 Views

### Dimensionality Reduction in Gaussian Process Models

Feb 25, 2007

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4976 Views

### Modelling Intra-Speaker Variability for Improved Speaker Recognition

Feb 25, 2007

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4780 Views

### Dimensionality Reduction by Feature Selection in Machine Learning

Feb 25, 2007

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17257 Views

### Semantic text features from small world graphs

Feb 25, 2007

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6553 Views

### Sparsity analsysis of term weighting schemes and application to text classificat...

Feb 25, 2007

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3437 Views

### Greedy Feature Grouping for Optimal Discriminant Subspaces

Feb 25, 2007

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3626 Views

### Constructing visual models with a latent space approach

Feb 25, 2007

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3082 Views

### What is the Optimal Number of Features? A learning theoretic perspective

Feb 25, 2007

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6904 Views

### A statistical learning approach to subspace identification of dynamical systems

Feb 25, 2007

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6735 Views

### Classification of high dimensional data: High Dimensional Discriminant Analysis

Feb 25, 2007

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4698 Views

### Random projection, margins, kernels, and feature-selection

Feb 25, 2007

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7688 Views

### A simple feature extraction for high dimensional image representations

Feb 25, 2007

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5246 Views

### Feature-Learning from Pairs of Examples in Collections of Supervised Learning Ta...

Feb 25, 2007

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3438 Views

### Identifying Feature Relevance using a Random Forest

Feb 25, 2007

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12613 Views

### Online feature selection for contextual time series data

Feb 25, 2007

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3528 Views