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1
Intro
2
Adaptive Sampling Example
3
Data Summarization Tasks
4
Streaming Algorithms
5
Results: L2.2 Sampling with Post-Processin
6
Outline of Results
7
Results: Adaptive Sampling
8
Applications: Row Subset Selection
9
Applications: Subspace Approximation
10
Applications: Projective Clustering
11
Applications: Volume Maximization
12
Volume Maximization Lower Bounds
13
Volume Maximization - Row Arrival
14
L2.2 Sampler with Post-Processing Matrix
15
L2,2 Sampler
16
Handling Post-Processing Matrix
17
Algorithm Using L22 Sampler
18
Bad Example
19
Intuition
Description:
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)
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