Toward a Unified Theory of Sparse Dimensionality Reduction in Euclidean Space

Author:

Bourgain Jean1,Dirksen Sjoerd2,Nelson Jelani3

Affiliation:

1. IAS, Princeton, NJ, USA

2. RWTH Aachen, Aachen, Germany

3. Harvard University, Cambridge, MA, USA

Funder

Office of Naval Research

Google

NSF

Deutsche Forschungsgemeinschaft

Publisher

ACM

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3. Krylov Methods are (nearly) Optimal for Low-Rank Approximation;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06

4. Oblivious dimension reduction for k -means: beyond subspaces and the Johnson-Lindenstrauss lemma;Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing;2019-06-23

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