Tensor Networks vs. PCA and PLS for High Dimensional Medical Datasets

Explore the comparison between Tensor Networks and traditional dimensionality reduction techniques like Principal Component Analysis (PCA) and Partial Least Squares (PLS) in this hour-long seminar. Delve into the quantum-inspired algorithms of tensor networks and contrast them with effective PCA and PLS algorithms used today. Gain valuable insights on when to apply Tensor Networks, PCA, or PLS to high-dimensional medical datasets. Learn about recent advancements in Tensor Networks, including their integration with neural networks, complementary benefits to FDA-approved AI/ML technologies, and improvements over competing methods in 2024 literature. Understand the challenges posed by the "curse of dimensionality" in high-dimensional data analysis and how these techniques address them. Benefit from references to recent studies and tutorials in biomedical data analysis, guided clustering, and machine learning practices in the medical field.

Tensor Networks vs. PCA and PLS for High Dimensional Medical Datasets