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

Home

Lecture

PAC Learning: Empirical Risk Minimization

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (49)

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.

Decision Trees: Classification Log in to Mediaspace to watch this video

Introduces decision trees for classification, covering entropy, split quality, Gini index, advantages, disadvantages, and the random forest classifier.

Data Mining: Introduction Log in to Mediaspace to watch this video

Covers the challenges and opportunities of data mining, practical questions, algorithm components, and applications like shopping basket analysis.

Perceptual Modeling: Understanding Spatial Thinking and Vision Log in to Mediaspace to watch this video

Examines perceptual modeling and spatial thinking in visual intelligence, exploring theories, cognitive maps, and the interplay between bottom-up and top-down processing.

Linear Regression: Basics and Gradient Descent Log in to Mediaspace to watch this video

Covers the basics of linear regression, including feature engineering, supervised vs. unsupervised learning, and minimizing the cost function.

Image Classification: Decision Trees & Random Forests Log in to Mediaspace to watch this video

Explores image classification using decision trees and random forests to reduce variance and improve model robustness.

Advanced Information Theory: F-Divergences and Generalization Error Log in to Mediaspace to watch this video

Covers f-divergences and generalization error in advanced information theory.

Kernel Ridge Regression: Equivalent Formulations and Representer Theorem Log in to Mediaspace to watch this video

Explores Kernel Ridge Regression, equivalent formulations, Representer Theorem, Kernel trick, and predicting with kernels.

Topic Models: Latent Dirichlet Allocation Log in to Mediaspace to watch this video

Covers topic models, focusing on Latent Dirichlet Allocation, clustering, GMMs, Dirichlet distribution, LDA learning, and applications in digital humanities.

Page 3 of 3