Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Home

Concept

Kernel (statistics)

Formal sciences
Statistics
Statistical inference
Non-parametric statistics

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (32)

Kernel Regression: Basics and Applications Log in to Mediaspace to watch this video

Explores kernel regression, the curse of dimensionality, and random features in neural networks.

Clustering & Density Estimation Log in to Mediaspace to watch this video

Covers dimensionality reduction, PCA, clustering techniques, and density estimation methods.

Clustering & Density Estimation Log in to Mediaspace to watch this video

Covers dimensionality reduction, clustering, and density estimation techniques, including PCA, K-means, GMM, and Mean Shift.

Kernel Regression: K-nearest Neighbors Log in to Mediaspace to watch this video

Covers the concept of kernel regression and K-nearest neighbors for making data linearly separable.

Neural Networks: Random Features and Kernel Regression Log in to Mediaspace to watch this video

Explores random features in neural networks and kernel regression using stochastic gradient descent.

Dimensionality Reduction: PCA and LDA Log in to Mediaspace to watch this video

Covers dimensionality reduction techniques like PCA and LDA, clustering methods, density estimation, and data representation.

Kernels: Nonlinear Transformations Log in to Mediaspace to watch this video

Explores kernels for simplifying data representation and making it linearly separable in feature spaces, including popular functions and practical exercises.

Feature Expansion and Kernels Log in to Mediaspace to watch this video

Covers feature expansion, kernels, SVM, and nonlinear classification in machine learning.

Learning the Kernel: Convex Optimization Log in to Mediaspace to watch this video

Explores learning the kernel function in convex optimization, focusing on predicting outputs using a linear classifier and selecting optimal kernel functions through cross-validation.

Feature Selection, Kernel Regression, Neural Networks Playground Log in to Mediaspace to watch this video

Covers feature selection, kernel regression, and neural networks through exercises.

Data Representation: BoW and Imbalanced Data Log in to Mediaspace to watch this video

Covers overfitting, model selection, validation, cross-validation, regularization, kernel regression, and data representation challenges.

Transformer Architectures: Subquadratic Attention Mechanisms Log in to Mediaspace to watch this video

Covers transformer architecture and subquadratic attention mechanisms, focusing on efficient approximations and their applications in machine learning.

Page 2 of 2