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Supervised Quantile Normalization for Matrix Factorization Using Optimal Transport

Offered By: VinAI via YouTube

Tags

Optimal Transport Courses Machine Learning Courses Genomics Courses Probability Distributions Courses Dimensionality Reduction Courses Matrix Factorization Courses Wasserstein Distances Courses

Course Description

Overview

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Explore a seminar on supervised quantile normalization for matrix factorization using optimal transport. Delve into the speaker's recent work applying regularized optimal transport to perform "soft" sorting and ranking. Learn about the expansion of this framework to include differentiable "soft" quantile normalization operators and their application to dimensionality reduction. Discover algorithms for normalizing features with target quantile distributions to obtain matrices that are easier to factorize. Examine empirical evidence of recovery and practical applications in genomics. Gain insights from Marco Cuturi, a Google Brain researcher with extensive experience in applied mathematics, statistics, and machine learning, particularly in optimal transport and Wasserstein distances.

Syllabus

[Seminar Series] Supervised Quantile Normalization for Matrix Factorization using Optimal Transport


Taught by

VinAI

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