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We design novel composable sketches for WOR `p sampling, weighted sampling of keys according to a power p ∈ [0, 2] of their frequency (or for signed data, sum ...
Jul 14, 2020 · We design novel composable sketches for WOR \ell_p sampling, weighted sampling of keys according to a power p\in[0,2] of their frequency.
Dec 6, 2020 · We design novel composable sketches for WOR ℓp sampling, weighted sampling of keys according to a power p ∈ [0,2] of their frequency (or for ...
We design novel composable sketches for WOR $\ell_p$ sampling, weighted sampling of keys according to a power $p\in[0,2]$ of their frequency (or for signed data ...
Edith Cohen, Rasmus Pagh, David P. Woodruff: WOR and p's: Sketches for ℓp-Sampling Without Replacement. NeurIPS 2020.
Dec 6, 2020 · Neural Information Processing Systems (NeurIPS) is a multi-track machine learning and computational neuroscience conference that includes ...
Our design is simple and practical, despite intricate analysis, and based on off-the-shelf use of widely implemented heavy hitters sketches such as CountSketch.
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Cohen, Edith, Pagh, Rasmus, and Woodruff, David P. WOR and p's: Sketches for ℓp-Sampling Without Replacement. Retrieved from https://par.nsf.gov/biblio/10249973 ...
We present novel composable sketches for without-replacement (WOR) `p sampling, based on ... 1-pass relative-error lp-sampling with applications. In. Proc. 21st ...
Aug 15, 2020 · When weight distributions are skewed, as is often the case in practice, without-replacement (WOR) sampling is much more effective than with- ...