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REPORTS > KEYWORD > EMBEDDING:
Reports tagged with Embedding:
TR07-012 | 22nd January 2007
Shachar Lovett, Sasha Sodin

#### Almost Euclidean sections of the N-dimensional cross-polytope using O(N) random bits

Revisions: 1

It is well known that $\R^N$ has subspaces of dimension
proportional to $N$ on which the $\ell_1$ norm is equivalent to the
$\ell_2$ norm; however, no explicit constructions are known.
Extending earlier work by Artstein--Avidan and Milman, we prove that
such a subspace can be generated using $O(N)$ random bits.

... more >>>

TR07-048 | 3rd April 2007
Alexandr Andoni, Piotr Indyk, Robert Krauthgamer

#### Earth Mover Distance over High-Dimensional Spaces

The Earth Mover Distance (EMD) between two equal-size sets
of points in R^d is defined to be the minimum cost of a
bipartite matching between the two pointsets. It is a natural metric
for comparing sets of features, and as such, it has received
significant interest in computer vision. Motivated ... more >>>

TR15-101 | 15th June 2015
Patrick Scharpfenecker

#### On the structure of Solution-Graphs for Boolean Formulas

Revisions: 2

In this work we extend the study of solution graphs and prove that for boolean formulas in a class called CPSS, all connected components are partial cubes of small dimension, a statement which was proved only for some cases in [Schwerdtfeger 2013]. In contrast, we show that general Schaefer formulas ... more >>>

TR15-111 | 8th July 2015
Diptarka Chakraborty, Elazar Goldenberg, Michal Koucky

#### Low Distortion Embedding from Edit to Hamming Distance using Coupling

Revisions: 1

The Hamming and the edit metrics are two common notions of measuring distances between pairs of strings $x,y$ lying in the Boolean hypercube. The edit distance between $x$ and $y$ is defined as the minimum number of character insertion, deletion, and bit flips needed for converting $x$ into $y$. ... more >>>

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