Search for tag: "dimensionality"

Anis Hamadouche Presentation - SSPD 2021

Presented at the Sensor Signal Processing for Defence Conference (SSPD) 2021Presentation: "Approximate Proximal-Gradient Methods" Speaker: Anis Hamadouche, Heriot-Watt…

From  Joe Burchell 0 likes 21 plays 0  

Edossa Merga Terefe EVA Talk Preview

This talk has captions. You can remove these by pressing CC on the video toolbar. Name: Edossa Merga Terefe Talk Title: Extremal Random Forests Abstract: Methods from statistics and machine…

From  Anna Munro 0 likes 22 plays 0  

ML2: Dimensionality Reduction

In this second video, we motivate why it is useful to reduce the dimensionality of your data, and describe how this can be done linearly, using a transformation matrix. We describe a setup whereby we…

From  Elliot Crowley 0 likes 18 plays 0  

MLP Lecture 07 - Clip 06 - Multiple Feature Maps

Machine Learning Practical (MLP) Lecture 07, Clip 06 / 09.

From  Pavlos Andreadis 1 likes 364 plays 0  

Unsupervised Learning

Unsupervised Learning

From  Dimitrios Doudesis 0 likes 300 plays 0  

Sampling

Sampling - Week 4

From  Calum Macphail 0 likes 116 plays 0  

Pros and cons of dimensionality reduction

Pros and cons of dimensionality reduction

From  Nigel Goddard 1 likes 2,589 plays 0  

How many principal components to use

How many principal components to use

From  Nigel Goddard 1 likes 2,138 plays 0  

Why we maximize variance in PCA

Why we maximize variance in PCA

From  Nigel Goddard 2 likes 2,943 plays 0  

Tackling the curse of dimensionality

Tackling the curse of dimensionality

From  Nigel Goddard 1 likes 2,560 plays 0  

The curse of dimensionality

The curse of dimensionality

From  Nigel Goddard 2 likes 2,547 plays 0  

Data manifolds in high-dimensional spaces

Data manifolds in high-dimensional spaces

From  Nigel Goddard 2 likes 2,537 plays 0  

Pros and cons of nearest-neighbor methods

Pros and cons of nearest-neighbor methods

From  Nigel Goddard 1 likes 3,600 plays 0