Complexity of Lasso with Normalized Data
Vladimir Dragovich explores the computational complexity aspects of Lasso regression when applied to normalized datasets, a relevant inquiry in statistical learning theory and machine learning.
Research Lab
UT Austin
Peer-curated academic archive from UT Austin, comprising 2 recorded lectures in AI & Machine Learning, Algorithms & Theoretical CS, Engineering, Control & Robotics.
University Courses
0
Standalone archive
Recorded Lectures
2
2 standalone talks
Archive Runtime
2h
Unabridged recordings
Faculty & Speakers
2
Avg rigor 91/100
Discipline:
Talks & colloquia from UT Austin
2Self-contained research seminars, public lectures, and invited colloquia.
Model Scale Versus Domain Knowledge in Long-Term Forecasting of Chaos
William Gilpin explores the interplay between model complexity and foundational domain understanding for robust long-term prediction in chaotic natural systems.
Faculty & visiting speakers at UT Austin
2Professors, researchers, and invited lecturers recorded at UT Austin.
All recorded lectures from UT Austin
2Browse, filter, and sort every lecture from UT Austin.
Showing 2 of 2 lectures
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Scholar · University
Chapters · Duration
59:53
45:04