1![Note to other teachers and users of these slides: We would be delighted if you found this our material useful in giving your own lectures. Feel free to use these slides verbatim, or to modify them to fit your own needs. Note to other teachers and users of these slides: We would be delighted if you found this our material useful in giving your own lectures. Feel free to use these slides verbatim, or to modify them to fit your own needs.](https://www.pdfsearch.io/img/abe9fca8b559b993e47e45e1fc82208f.jpg) | Add to Reading ListSource URL: mmds.orgLanguage: English - Date: 2014-08-11 14:08:00
|
---|
2![8 The Lanczos Method Erik Koch Computational Materials Science German Research School for Simulation Sciences 8 The Lanczos Method Erik Koch Computational Materials Science German Research School for Simulation Sciences](https://www.pdfsearch.io/img/e15aae0cc55025d4cb8d62f84ff8b0a1.jpg) | Add to Reading ListSource URL: www.cond-mat.deLanguage: English - Date: 2014-05-26 12:52:54
|
---|
3![IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. X, NO. X, MONTH 20XX 1 Joint Speaker Verification and Anti-Spoofing in the i-Vector Space IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. X, NO. X, MONTH 20XX 1 Joint Speaker Verification and Anti-Spoofing in the i-Vector Space](https://www.pdfsearch.io/img/afa93e31409d0d0267f61bc2a3f8f8af.jpg) | Add to Reading ListSource URL: www.cstr.inf.ed.ac.ukLanguage: English - Date: 2015-09-29 11:06:25
|
---|
4![Contents 1 Singular Value Decomposition (SVD) 1.1 Singular Vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Singular Value Decomposition (SVD) . . . . . . . . . . . . . . . . . 1.3 Best Rank k Approx Contents 1 Singular Value Decomposition (SVD) 1.1 Singular Vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Singular Value Decomposition (SVD) . . . . . . . . . . . . . . . . . 1.3 Best Rank k Approx](https://www.pdfsearch.io/img/fbb90b8ea2c84f52591712bb1b44c1dc.jpg) | Add to Reading ListSource URL: www.cs.cmu.eduLanguage: English - Date: 2012-03-06 21:36:15
|
---|
5![Odyssey 2012 The Speaker and Language Recognition WorkshopJune 2012, Singapore Speaker vectors from Subspace Gaussian Mixture Model as complementary features for Language Identification Odyssey 2012 The Speaker and Language Recognition WorkshopJune 2012, Singapore Speaker vectors from Subspace Gaussian Mixture Model as complementary features for Language Identification](https://www.pdfsearch.io/img/e09e0961e5026e934ec621e421ecc92b.jpg) | Add to Reading ListSource URL: www.fit.vutbr.czLanguage: English - Date: 2012-07-17 03:17:15
|
---|
6![CS 1173: MATLAB min function The min function returns the minimum value of the elements along an array dimension. B = min(A, [], dim) minimum elements CS 1173: MATLAB min function The min function returns the minimum value of the elements along an array dimension. B = min(A, [], dim) minimum elements](https://www.pdfsearch.io/img/1e4205dd0eb9cf0f06000e1b47c2a781.jpg) | Add to Reading ListSource URL: www.cs.utsa.eduLanguage: English - Date: 2009-09-22 20:25:08
|
---|
7![Pattern-Guided k-Anonymity Pattern-Guided k-Anonymity](https://www.pdfsearch.io/img/0e7aa9b46945e79f894967cdc22bc5bf.jpg) | Add to Reading ListSource URL: fpt.akt.tu-berlin.deLanguage: English - Date: 2013-10-21 04:21:43
|
---|
8![CS 1173: MATLAB sum function The sum function returns the sum along an array dimension. B = sum(A, dim) resulting sum CS 1173: MATLAB sum function The sum function returns the sum along an array dimension. B = sum(A, dim) resulting sum](https://www.pdfsearch.io/img/603b9c0e2ae6663610f4cf3524ca278f.jpg) | Add to Reading ListSource URL: www.cs.utsa.eduLanguage: English - Date: 2012-09-03 20:54:14
|
---|
9![CS 1173: MATLAB max function The max function returns the maximum value of the elements along an array dimension. B = max(A, [], dim) maximum elements CS 1173: MATLAB max function The max function returns the maximum value of the elements along an array dimension. B = max(A, [], dim) maximum elements](https://www.pdfsearch.io/img/0f67b8f427e9ff61c924fdf86caf3cf2.jpg) | Add to Reading ListSource URL: www.cs.utsa.eduLanguage: English - Date: 2009-09-22 20:23:56
|
---|
10![[removed]The Basic Method Proof of Claim[removed]Suppose not. Then for some v, v 0 ∈ A we have u + v = u0 + v 0 , and hence, v + v 0 = u + u0 . Let c, c0 be the vectors from C for which [removed]The Basic Method Proof of Claim[removed]Suppose not. Then for some v, v 0 ∈ A we have u + v = u0 + v 0 , and hence, v + v 0 = u + u0 . Let c, c0 be the vectors from C for which](https://www.pdfsearch.io/img/a557a8a6752dd11eca09f08722f1de96.jpg) | Add to Reading ListSource URL: lovelace.thi.informatik.uni-frankfurt.deLanguage: English - Date: 2007-08-30 03:42:28
|
---|