Explore non-adaptive adaptive sampling techniques for turnstile streams in this 25-minute conference talk. Delve into adaptive sampling examples, data summarization tasks, and streaming algorithms. Examine results for L2.2 sampling with post-processing and adaptive sampling. Discover applications in row subset selection, subspace approximation, projective clustering, and volume maximization. Learn about volume maximization lower bounds and row arrival scenarios. Understand the L2,2 sampler with post-processing matrix, its algorithm, and potential pitfalls through a bad example. Gain insights into the intuition behind these techniques for efficient data stream processing.
Non-Adaptive Adaptive Sampling on Turnstile Streams
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
Intro
Adaptive Sampling Example
Data Summarization Tasks
Streaming Algorithms
Results: L2.2 Sampling with Post-Processin
Outline of Results
Results: Adaptive Sampling
Applications: Row Subset Selection
Applications: Subspace Approximation
Applications: Projective Clustering
Applications: Volume Maximization
Volume Maximization Lower Bounds
Volume Maximization - Row Arrival
L2.2 Sampler with Post-Processing Matrix
L2,2 Sampler
Handling Post-Processing Matrix
Algorithm Using L22 Sampler
Bad Example
Intuition
Taught by
Association for Computing Machinery (ACM)
