Cbcb:Pop-Lab:Mohammad-Report: Difference between revisions
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Known bounds for embedding Levenstein distance into metric spaces | |||
*[http://portal.acm.org/citation.cfm?id=1109557.1109669 Lower bound of <math>\Omega(\log n)</math> where n is number of points | *[http://portal.acm.org/citation.cfm?id=1109557.1109669 Lower bound of <math>\Omega(\log n)</math> where n is number of points] | ||
*[http://portal.acm.org/citation.cfm?id=1284322 Upper bound of <math>2^{O(\sqrt(log d log log d))}</math> where d is dimension (i.e. length) | *[http://portal.acm.org/citation.cfm?id=1284322 Upper bound of <math>2^{O(\sqrt(\log d \log \log d))}</math> where d is dimension (i.e. length)] | ||
FFT and random projections | FFT and random projections | ||
*[https://wiki.umiacs.umd.edu/cbcb/images/f/f6/Projection.pdf Presentation] | *[https://wiki.umiacs.umd.edu/cbcb/images/f/f6/Projection.pdf Presentation] | ||
*[https://wiki.umiacs.umd.edu/cbcb/images/1/13/Fft2.pdf Writeup] | *[https://wiki.umiacs.umd.edu/cbcb/images/1/13/Fft2.pdf Writeup] | ||
Latest revision as of 17:40, 11 March 2009
Known bounds for embedding Levenstein distance into metric spaces
- Lower bound of <math>\Omega(\log n)</math> where n is number of points
- Upper bound of <math>2^{O(\sqrt(\log d \log \log d))}</math> where d is dimension (i.e. length)
FFT and random projections