Under the auspices of the Computational Complexity Foundation (CCF)

REPORTS > KEYWORD > SAMPLING:
Reports tagged with Sampling:
TR97-020 | 15th May 1997
Oded Goldreich

#### A Sample of Samplers -- A Computational Perspective on Sampling (survey).

We consider the problem of estimating the average of a huge set of values.
That is,
given oracle access to an arbitrary function $f:\{0,1\}^n\mapsto[0,1]$,
we need to estimate $2^{-n} \sum_{x\in\{0,1\}^n} f(x)$
upto an additive error of $\epsilon$.
We are allowed to employ a randomized algorithm which may ... more >>>

TR98-032 | 10th June 1998
Mihir Bellare, Oded Goldreich, Erez Petrank

#### Uniform Generation of NP-witnesses using an NP-oracle.

A Uniform Generation procedure for $NP$ is an
algorithm which given any input in a fixed NP-language, outputs a uniformly
distributed NP-witness for membership of the input in the language.
We present a Uniform Generation procedure for $NP$ that runs in probabilistic
polynomial-time with an NP-oracle. This improves upon ... more >>>

TR98-058 | 2nd August 1998
H. Buhrman, Dieter van Melkebeek, K.W. Regan, Martin Strauss, D. Sivakumar

#### A Generalization of Resource-Bounded Measure, With Application to the BPP vs. EXP Problem

We introduce "resource-bounded betting games", and propose
a generalization of Lutz's resource-bounded measure in which the choice
of next string to bet on is fully adaptive. Lutz's martingales are
equivalent to betting games constrained to bet on strings in lexicographic
order. We show that if strong pseudo-random number generators exist,
more >>>

TR01-027 | 23rd March 2001
Marius Zimand

#### Probabilistically Checkable Proofs The Easy Way

We present a weaker variant of the PCP Theorem that admits a
significantly easier proof. In this
variant the prover only has $n^t$ time to compute each
bit of his answer, for an arbitray but fixed constant
$t$, in contrast to
being all powerful. We show that
3SAT ... more >>>

TR03-037 | 30th April 2003
Ziv Bar-Yossef

#### Sampling Lower Bounds via Information Theory

We present a novel technique, based on the Jensen-Shannon divergence
from information theory, to prove lower bounds on the query complexity
of sampling algorithms that approximate functions over arbitrary
domain and range. Unlike previous methods, our technique does not
use a reduction from a binary decision problem, but rather ... more >>>

TR07-015 | 1st March 2007
Oded Goldreich, Or Sheffet

#### On the randomness complexity of property testing

We initiate a general study of the randomness complexity of
property testing, aimed at reducing the randomness complexity of
testers without (significantly) increasing their query complexity.
One concrete motovation for this study is provided by the
observation that the product of the randomness and query complexity
of a tester determine ... more >>>

TR10-170 | 11th November 2010
Scott Aaronson, Alex Arkhipov

#### The Computational Complexity of Linear Optics

We give new evidence that quantum computers -- moreover, rudimentary quantum computers built entirely out of linear-optical elements -- cannot be efficiently simulated by classical computers. In particular, we define a
model of computation in which identical photons are generated, sent through a linear-optical network, then nonadaptively measured to count ... more >>>

TR11-056 | 14th April 2011
Emanuele Viola

#### Extractors for circuit sources

We obtain the first deterministic extractors for sources generated (or sampled) by small circuits of bounded depth. Our main results are:

(1) We extract $k (k/nd)^{O(1)}$ bits with exponentially small error from $n$-bit sources of min-entropy $k$ that are generated by functions $f : \{0,1\}^\ell \to \{0,1\}^n$ where each output ... more >>>

TR12-042 | 17th April 2012
Chris Beck, Russell Impagliazzo, Shachar Lovett

#### Large Deviation Bounds for Decision Trees and Sampling Lower Bounds for AC0-circuits

There has been considerable interest lately in the complexity of distributions. Recently, Lovett and Viola (CCC 2011) showed that the statistical distance between a uniform distribution over a good code, and any distribution which can be efficiently sampled by a small bounded-depth AC0 circuit, is inverse-polynomially close to one. That ... more >>>

TR12-047 | 24th April 2012
Emanuele Viola

#### Extractors for Turing-machine sources

We obtain the first deterministic randomness extractors
for $n$-bit sources with min-entropy $\ge n^{1-\alpha}$
generated (or sampled) by single-tape Turing machines
running in time $n^{2-16 \alpha}$, for all sufficiently
small $\alpha > 0$. We also show that such machines
cannot sample a uniform $n$-bit input to the Inner
Product function ... more >>>

TR15-205 | 15th December 2015
Emanuele Viola

#### Quadratic maps are hard to sample

This note proves the existence of a quadratic GF(2) map
$p : \{0,1\}^n \to \{0,1\}$ such that no constant-depth circuit
of size $\poly(n)$ can sample the distribution $(u,p(u))$
for uniform $u$.

more >>>

TR17-166 | 3rd November 2017
Emanuele Viola

#### A sampling lower bound for permutations

A map $f:[n]^{\ell}\to[n]^{n}$ has locality $d$ if each output symbol
in $[n]=\{1,2,\ldots,n\}$ depends only on $d$ of the $\ell$ input
symbols in $[n]$. We show that the output distribution of a $d$-local
map has statistical distance at least $1-2\cdot\exp(-n/\log^{c^{d}}n)$
from a uniform permutation of $[n]$. This seems to be the ... more >>>

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