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The Taiping Rebellion

The Taiping Rebellion

The Taiping Rebellion. By: Joseph Randles. Overview. The Taiping Rebellion was a rebellion started by a fanatical religious sect of christianity lasting from 1850 to 1864 The fighting lead to an estimated 20 million soldier and civilian lives

By amanda
(1248 views)


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Sparse Recovery ( Using Sparse Matrices)

Sparse Recovery ( Using Sparse Matrices)

Sparse Recovery ( Using Sparse Matrices). Piotr Indyk MIT. Heavy Hitters. Also called frequent elements and elephants Define HH p φ ( x ) = { i : |x i | ≥ φ || x|| p } L p Heavy Hitter Problem: Parameters: φ and φ ’ (often φ ’ = φ - ε )

By chaney (137 views)

Sparse Recovery Using Sparse (Random) Matrices

Sparse Recovery Using Sparse (Random) Matrices

Sparse Recovery Using Sparse (Random) Matrices. Piotr Indyk MIT. Joint work with: Radu Berinde, Anna Gilbert, Howard Karloff, Martin Strauss and Milan Ruzic. Ax. A. =. x. x. x*. k=2. Linear Compression (a.k.a. linear sketching, compressed sensing). Setup:

By rodriguezm (0 views)

Sparse LA

Sparse LA

Sparse LA. Sathish Vadhiyar. Motivation. Sparse computations much more challenging than dense due to complex data structures and memory references Many physical systems produce sparse matrices. Sparse Matrix-Vector Multiplication. Cache in GPUs.

By dawn (271 views)

Sparse Matrices

Sparse Matrices

Sparse Matrices. sparse … many elements are zero dense … few elements are zero. Example Of Sparse Matrices. diagonal tridiagonal lower triangular (?) These are structured sparse matrices. May be mapped into a 1D array so that a mapping function can be used to locate an element.

By erek (169 views)

Sparse Recovery Using Sparse (Random) Matrices

Sparse Recovery Using Sparse (Random) Matrices

Sparse Recovery Using Sparse (Random) Matrices. Piotr Indyk MIT. Joint work with: Radu Berinde, Anna Gilbert, Howard Karloff, Martin Strauss and Milan Ruzic. Ax. A. =. x. x. x*. k=2. Linear Compression (a.k.a. linear sketching, compressed sensing). Setup:

By bona (266 views)

Sparse Recovery Using Sparse (Random) Matrices

Sparse Recovery Using Sparse (Random) Matrices

Sparse Recovery Using Sparse (Random) Matrices. Piotr Indyk MIT. Joint work with: Radu Berinde, Anna Gilbert, Howard Karloff, Martin Strauss and Milan Ruzic. Goal of this talk. “Stay awake until the end”. Ax. A. =. x. x. x*. k=2.

By adrina (157 views)

Sparse Matrices

Sparse Matrices

Sparse Matrices. sparse … many elements are zero dense … few elements are zero. Example Of Sparse Matrices. diagonal tridiagonal lower triangular (?) These are structured sparse matrices. May be mapped into a 1D array so that a mapping function can be used to locate an element.

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Sparse Representation

Sparse Representation

Sparse Representation. Shih-Hsiang Lin ( 林士翔 ). 1. T. N. Sainath , et al., “Bayesian Compressive Sensing for Phonetic Classification,” ICASSP 2010

By shima (145 views)

Sparse Matrices

Sparse Matrices

Sparse Matrices. Matrix  table of values. 0 0 3 0 4 0 0 5 7 0 0 0 0 0 0 0 2 6 0 0. Row 2. Column 4. Sparse Matrices. Matrix  table of values. 4 x 5 matrix 4 rows 5 columns 20 elements 6 nonzero elements. Sparse Matrices.

By thi (192 views)

Sparse Matrices

Sparse Matrices

Sparse Matrices. Matrix  table of values. 0 0 3 0 4 0 0 5 7 0 0 0 0 0 0 0 2 6 0 0. Row 2. Column 4. Sparse Matrices. Matrix  table of values. 4 x 5 matrix 4 rows 5 columns 20 elements 6 nonzero elements. Sparse Matrices.

By tappling (0 views)