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Lower Bounds for Sparse Oblivious Subspace Embeddings

Summary: Proves tight lower bounds for sparse oblivious subspace embeddings: any OSE with one nonzero per column requires m = Ω(d^2/(ε^2 δ)), implying Count-Sketch is optimal. For 1/(9ε) nonzeros/column they show m = Ω(ε^{O(δ)} d^2), improving prior Ω(ε^2 d^2). (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1861
Venue
PODS
Year
2022
Pagerank
4.1945683e-05
Overall Rank
11,330 | 21.18%
DOI
10.1145/3517804.3526224

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
140 The MADlib Analytics Library or MAD Skills, the SQL 2012 VLDB 0.00042270404
834 Learning Linear Regression Models over Factorized Joins 2016 SIGMOD 0.00016135159
6,914 Private Incremental Regression 2017 PODS 4.8925595e-05
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