Supervised Quantile Normalization for Matrix Factorization Using Optimal Transport
Offered By: VinAI via YouTube
Course Description
Overview
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
Related Courses
機率 (Probability)National Taiwan University via Coursera Einführung in die Wahrscheinlichkeitstheorie
Johannes Gutenberg University Mainz via iversity Probabilidad básica
Universidad Politécnica de Cartagena via Miríadax Probability And Statistics
Indian Institute of Technology, Kharagpur via Swayam Modeling Risk and Realities
University of Pennsylvania via Coursera