Curse of Dimensionality Courses and Certifications

Data Science Dojo

VSM, LSA, & SVD - Introduction to Text Analytics with R

Explore advanced text analytics techniques: VSM, LSA, and SVD. Learn to handle high-dimensional data, uncover latent semantic structures, and efficiently map new data in reduced dimensions.

• YouTube
• 38 minutes
• On-Demand
• Free Video

Alan Turing Institute

Optimal Sampling in Weighted Least-Squares Methods - Application to High-Dimensional Approximation

Explore optimal sampling in weighted least-squares for high-dimensional approximation, focusing on mathematical foundations and modern approaches to overcome the curse of dimensionality.

• YouTube
• 48 minutes
• On-Demand
• Free Video

Alan Turing Institute

Multilevel Weighted Least Squares Polynomial Approximation – Sören Wolfers, KAUST

Explore multilevel weighted least squares polynomial approximation for high-dimensional function reconstruction, addressing the curse of dimensionality and leveraging structural assumptions for improved accuracy.

• YouTube
• 37 minutes
• On-Demand
• Free Video

Alan Turing Institute

Score Estimation with Infinite-Dimensional Exponential Families – Dougal Sutherland, UCL

Explore score estimation in infinite-dimensional exponential families, covering reproducing kernel Hilbert spaces, maximum likelihood, and Nystrom approximation. Includes theoretical overview and experimental results.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Dimensionality Reduction in Python

13 ratings at DataCamp

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Institute for Advanced Study

Overcoming the Curse of Dimensionality and Mode Collapse - Ke Li

Explore techniques to overcome dimensionality challenges and mode collapse in deep learning, focusing on GANs, maximum likelihood estimation, and efficient algorithms for high-dimensional spaces.

• YouTube
• 33 minutes
• On-Demand
• Free Video

BIMSA

Computational Quantum Mechanics in Phase Space - An Attempt to Break the Curse of Dimensionality

Explore computational quantum mechanics in phase space, focusing on breaking the curse of dimensionality through grid-based and particle-based methods for high-dimensional Wigner quantum dynamics simulations.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Hausdorff Center for Mathematics

Random Tessellation Forests: Overcoming the Curse of Dimensionality

Explore random tessellation forests in machine learning, overcoming dimensionality challenges through innovative partitioning methods and directional distributions for improved statistical performance.

• YouTube
• 58 minutes
• On-Demand
• Free Video

Center for Language & Speech Processing(CLSP), JHU

Facing the Curse of Dimensionality in Statistical Language Modeling using Distributed Representations

Discover how Yoshua Bengio tackles the curse of dimensionality in statistical language modeling through innovative distributional approaches and neural network techniques.

• YouTube
• 1 hour 26 minutes
• On-Demand
• Free Video

Data Science Dojo

N-Grams - Introduction to Text Analytics with R

Explore N-grams in text analytics, including TF-IDF validation, word ordering, dimensionality challenges, and hardware limitations. Enhance your R-based text analysis skills.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Steve Brunton

Sparse Nonlinear Dynamics Models with SINDy - The Library of Candidate Nonlinearities

Explores advanced techniques for SINDy algorithm, including control variables, bifurcation parameters, rational functions, dimensionality reduction, and symmetry constraints in nonlinear dynamics modeling.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Fields Institute

Deep Learning - Machine Learning and Dynamical Systems

Explore cutting-edge research connecting deep learning with dynamical systems through expert presentations on neural networks, control theory, and mathematical foundations.

• YouTube
• 4 hours 59 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Generalization Theory in Machine Learning

Explore generalization theory in machine learning, covering traditional methods, deep learning, and statistical learning theory. Gain insights into overcoming the curse of dimensionality and understanding learning bounds.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

Institute for Advanced Study

Emergent Linguistic Structure in Deep Contextual Neural Word Representations - Chris Manning

Explore emergent linguistic structures in deep neural word representations with Stanford's Chris Manning, examining language models, attention mechanisms, and vector space analysis.

• YouTube
• 43 minutes
• On-Demand
• Free Video

Institut des Hautes Etudes Scientifiques (IHES)

The Quest for Adaptivity in Machine Learning - Comparing Popular Methods

Explore supervised learning algorithms' strengths and weaknesses, comparing k-nearest-neighbor, kernel methods, and neural networks for adaptivity and performance across various problems.

• YouTube
• 32 minutes
• On-Demand
• Free Video