Randomized Numerical Linear Algebra (randNLA) on Sliding Windows
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Why randNLA on Sliding Windows?
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Results: Sliding Window Model
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Challenges
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Reverse Online Leverage Scores
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Algorithm
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Spectral Sparsification (Summary)
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Low-Rank Approximation
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Template
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Reverse Online l1 Sensitivities
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Results: Online Model
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Results: Connections
Description:
Explore cutting-edge research in randomized numerical linear algebra applied to streaming and sliding window models in this 24-minute IEEE conference talk. Delve into the challenges and solutions for near-optimal linear algebra techniques, including reverse online leverage scores, spectral sparsification, and low-rank approximation. Learn about the connections between online and sliding window models, and discover how these advanced algorithms can be applied to real-world data processing scenarios.
Near Optimal Linear Algebra in the Online and Sliding Window Models