Larry Wasserman - Robust Topological Inference
Offered By: Applied Algebraic Topology Network via YouTube
Course Description
Overview
Explore robust topological inference in this 54-minute lecture by Larry Wasserman. Delve into key concepts including persistence, target distribution, and distance to miss. Learn about effort results, self-confidence, and confidence bands. Examine bootstrap techniques and their comparison to bottleneck methods. Discover optimal tuning parameters and their application in real-world examples. Gain valuable insights into this complex topic, concluding with a Q&A session to reinforce understanding.
Syllabus
Introduction
Motivation
Persistence
Target Distribution
Distance to Miss
Effort Result
Selfconfidence
Confidence band
Bootstrap
Bootstrap vs bottleneck
Tuning parameters
Optimal tuning
Example
Conclusions
Questions
Taught by
Applied Algebraic Topology Network
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