Timeline for How to sample uniformly from singular matrices
Current License: CC BY-SA 3.0
6 events
when toggle format | what | by | license | comment | |
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Mar 15, 2014 at 3:06 | history | edited | Bill Bradley | CC BY-SA 3.0 |
Extended numerical experiments and accelerated rejection algorithm
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Jan 31, 2014 at 20:13 | comment | added | Stephan Müller | @Bill Its pure engineering, its good to hold as much as possible in CPU's cache. Depending on implementation either row- or column-access is good in its memory access pattern while the other is unfavorable. However by transposing one factor, you can work cache optimal. This sounds as a minor detail, but from a performance point of view its not. | |
Jan 31, 2014 at 15:59 | comment | added | Bill Bradley | @Stephan Müller How can you speed up the multiplication by transposing them? That sounds interesting. | |
Jan 30, 2014 at 21:58 | comment | added | marshall | arxiv.org/pdf/math/0511636v1.pdf has another approach for solving these sorts of problem exactly for small matrices. | |
Jan 30, 2014 at 18:21 | comment | added | Stephan Müller | I like the simultaneous singularity check of $M_1, ..., M_k$. You could also use some of them transposed for even faster multiplication. | |
Jan 30, 2014 at 15:16 | history | answered | Bill Bradley | CC BY-SA 3.0 |