Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: LSH on the Hypercube Revisited   LSH (locality sensitive hashing) had emerged as a powerful technique in
nearest-neighbor search in high dimensions [IM98, HIM12]. Given a point set $P$
in a metric space, and given parameters $r$ and $\varepsilon > 0$, the task is
to preprocess the point set, such that given a query point $q$, one can quickly
decide if $q$ is in distance at most $\leq r$ or $\geq (1+\varepsilon)r$ from
the point set $P$. Once such a near-neighbor data-structure is available, one
can reduce the general nearest-neighbor search to logarithmic number of queries
in such structures [IM98, Har01, HIM12].
  In this note, we revisit the most basic settings, where $P$ is a set of
points in the binary hypercube $\{0,1\}^d$, under the $L_1$/Hamming metric, and
present a short description of the LSH scheme in this case. We emphasize that
there is no new contribution in this note, except (maybe) the presentation
itself, which is inspired by the authors recent work [HM17].

33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
23
The categories of this paper are: solv-int