The power of online thinning in reducing discrepancy
DOI10.1007/s00440-018-0860-yzbMath1421.68246arXiv1608.02895OpenAlexW2963541004WikidataQ129643582 ScholiaQ129643582MaRDI QIDQ2416548
Ori Gurel-Gurevich, Aaditya Ramdas, Raaz Dwivedi, Ohad Noy Feldheim
Publication date: 23 May 2019
Published in: Probability Theory and Related Fields (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1608.02895
Geometric probability and stochastic geometry (60D05) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55) Online algorithms; streaming algorithms (68W27) Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) (68Q87)
Cites Work
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- Choices, intervals and equidistribution
- On the small ball inequality in all dimensions
- The asymptotic behavior of spacings under Kakutani's model for interval subdivision
- A proof of Kakutani's conjecture on random subdivision of longest intervals
- Davenport's theorem in the theory of irregularities of point distribution
- Weak convergence results for the Kakutani interval splitting procedure.
- The power of thinning in balanced allocation
- Choices and intervals
- Explicit constructions in the classical mean squares problem in irregularities of point distribution
- Harmonic analysis on totally disconnected groups and irregularities of point distributions
- Graphical balanced allocations and the (1 + β)-choice process
- Balanced Allocations
- Balanced Allocations: A Simple Proof for the Heavily Loaded Case
- Roth’s Orthogonal Function Method in Discrepancy Theory and Some New Connections
- Discrepancy Theory and Quasi-Monte Carlo Integration
- High-dimensional integration: The quasi-Monte Carlo way
- Balanced Allocations: The Heavily Loaded Case
- Justification and Extension of Doob's Heuristic Approach to the Kolmogorov- Smirnov Theorems
- On irregularities of distribution
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