Explore cutting-edge research on learning-augmented sketches for frequency estimation in this 46-minute lecture by Piotr Indyk from the Massachusetts Institute of Technology. Delve into the intersection of sublinear algorithms and nearest-neighbor search as part of the Simons Institute's series on advanced computational techniques. Gain insights into how machine learning can enhance traditional sketching methods for more efficient and accurate frequency estimation in large datasets.
Learning-Augmented Sketches for Frequency Estimation
Overview
Syllabus
Learning-Augmented Sketches for Frequency Estimation
Taught by
Simons Institute
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