Low-Rank Approximation Courses and Certifications

Institute for Pure & Applied Mathematics (IPAM)

Low Rank Approximation in Electron Excitation Calculations - IPAM at UCLA

Explore low rank approximation techniques for efficient electron excitation calculations, focusing on the Interpolative Separable Density Fitting method and its applications in quantum mechanics.

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

IEEE

Robust and Sample Optimal Algorithms for PSD Low-Rank Approximation

Explore efficient algorithms for positive semidefinite low-rank approximation, focusing on robustness and sample optimality in matrix computations.

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

International Centre for Theoretical Sciences

Sampling, Privacy, and Spectral Geometry - Insights from Low-Rank Approximation

Explore connections between sampling algorithms, privacy preservation, and spectral geometry through low-rank approximation techniques in this advanced mathematical discussion.

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

Simons Institute

Advanced Techniques for Low-Rank Matrix Approximation

Explore cutting-edge methods for low-rank matrix approximation, including randomized algorithms and factorizations, with insights on efficiency and accuracy comparisons.

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

IEEE

Residual Based Sampling for Online Low Rank Approximation

Explore online low rank approximation through residual-based sampling, covering PCA, column subset selection, and online algorithms. Learn techniques for efficient data analysis and clustering.

• YouTube
• 23 minutes
• On-Demand
• Conference Talk

NHR@FAU

The Comedy Club of High-Performance Computing: Low-Rank Matrix Approximation Takes the Stage

Explore high-performance computing implementation of Tile Low-Rank Matrix-Vector Multiplication, its applications in seismic processing and astronomy, and performance advantages over dense implementations.

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

Society for Industrial and Applied Mathematics

Low Rank Tensor Completion and Its Applications

Explore low rank tensor completion methods using framelet, dictionary coding, deep plug-and-play prior, and more. Gain insights into theoretical and numerical results for solving complex imaging problems.

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

Simons Institute

Quantum-Inspired Classical Linear Algebra

Explore quantum-inspired classical algorithms for linear algebra, including sketching, sampling, and low-rank approximation techniques in this advanced computational talk.

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

Simons Institute

Sampling for Linear Algebra, Statistics, and Optimization I

Explore randomized numerical linear algebra techniques for efficient data analysis, covering sampling methods, matrix multiplication, and regression algorithms.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Simons Institute

Foundations of Data Science II

Explore advanced data science concepts including SVD, Gaussian mixtures, and Markov chains. Learn about randomized algorithms and low-rank approximations for efficient data handling.

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

Institute for Pure & Applied Mathematics (IPAM)

Learning-Based Low-Rank Approximations - IPAM at UCLA

Explores learning-based algorithms for low-rank matrix approximation, focusing on optimizing sketching matrices using training data to significantly reduce approximation errors in efficient computational methods.

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

IEEE

Near Optimal Linear Algebra in the Online and Sliding Window Models

Explore near-optimal linear algebra techniques for streaming and sliding window models, focusing on randomized algorithms and their applications in data analysis.

• YouTube
• 24 minutes
• On-Demand
• Conference Talk

Institute for Pure & Applied Mathematics (IPAM)

Arbitrary Tensor Network Algorithm: Theory, Methods and Applications

Explore arbitrary tensor network algorithms for complex systems modeling, covering theory, methods, and applications in probabilistic graphical models and quantum circuit simulations.

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

Institute for Pure & Applied Mathematics (IPAM)

Memory-Efficient Modewise Measurements for Tensor Compression and Recovery

Explores memory-efficient modewise measurements for tensor data processing, including compressed CP rank fitting and recovery techniques for low Tucker rank tensors.

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

Institut Henri Poincaré

When Your Big Data Seems Too Small: Accurate Inferences Beyond the Empirical Distribution - Part 2

Explore advanced techniques for accurate distribution inferences with limited data. Learn to de-noise empirical distributions, estimate population spectra, and recover low-rank matrix approximations.

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