Towards Optimal Moment Estimation in Streaming and Distributed Models
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Publication:6051992
DOI10.1145/3596494OpenAlexW2979234330MaRDI QIDQ6051992
Rajesh Jayaram, David P. Woodruff
Publication date: 23 October 2023
Published in: ACM Transactions on Algorithms (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1145/3596494
Cites Work
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- Space-efficient estimation of statistics over sub-sampled streams
- An information statistics approach to data stream and communication complexity
- Approximate counting: a detailed analysis
- Pseudorandom generators for space-bounded computation
- Optimal tracking of distributed heavy hitters and quantiles
- Corrigendum to: ``A second look at counting triangles in graph streams
- Randomized algorithms for tracking distributed count, frequencies, and ranks
- A Tight Lower Bound for High Frequency Moment Estimation with Small Error
- Zero-one frequency laws
- Computational Advertising: Techniques for Targeting Relevant Ads
- An Optimal Algorithm for Large Frequency Moments Using O(n^(1-2/k)) Bits
- Optimal Random Sampling from Distributed Streams Revisited
- Algorithms for distributed functional monitoring
- Sparser Johnson-Lindenstrauss Transforms
- The Simultaneous Communication of Disjointness with Applications to Data Streams
- Stable distributions, pseudorandom generators, embeddings, and data stream computation
- Optimal approximations of the frequency moments of data streams
- Functional Monitoring without Monotonicity
- Hellinger Strikes Back: A Note on the Multi-party Information Complexity of AND
- Counting large numbers of events in small registers
- Compressed Counting
- An Optimal Lower Bound on the Communication Complexity of Gap-Hamming-Distance
- Continuous Monitoring of l_p Norms in Data Streams
- Univariate Stable Distributions
- The Data Stream Space Complexity of Cascaded Norms
- Optimal principal component analysis in distributed and streaming models
- Tighter Low-rank Approximation via Sampling the Leveraged Element
- Relative Errors for Deterministic Low-Rank Matrix Approximations
- Asymptotically Optimal Lower Bounds on the NIH-Multi-Party Information Complexity of the AND-Function and Disjointness
- Tight bounds for distributed functional monitoring
- Fast moment estimation in data streams in optimal space
- Streaming Algorithms via Precision Sampling
- Turning Big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering
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