All reports by Author Alexander E. Andreev:

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TR00-053
| 5th May 2000
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Alexander E. Andreev, Andrea E. F. Clementi, Paolo Penna, Jose' D. P. Rolim#### Parallel Read Operations Without Memory Contention

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TR97-053
| 10th November 1997
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Alexander E. Andreev, J. L. Baskakov, Andrea E. F. Clementi, Jose' D. P. Rolim#### Small Random Sets for Affine Spaces and Better Explicit Lower Bounds for Branching Programs

Revisions: 2

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TR97-011
| 7th April 1997
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Alexander E. Andreev, Andrea E. F. Clementi, Jose' D.P. Rolim and Trevisan#### Weak Random Sources, Hitting Sets, and BPP Simulations

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TR96-055
| 22nd October 1996
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Alexander E. Andreev, Andrea E. F. Clementi, Jose' D. P. Rolim#### Hitting Properties of Hard Boolean Operators and their Consequences on BPP

Revisions: 1
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Comments: 1

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TR96-029
| 16th April 1996
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Alexander E. Andreev, Andrea E. F. Clementi, Jose' D. P. Rolim#### Towards efficient constructions of hitting sets that derandomize BPP

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TR95-061
| 27th November 1995
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Alexander E. Andreev, Andrea E. F. Clementi, Jose' D. P. Rolim#### Hitting sets derandomize BPP

Revisions: 1

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TR95-041
| 28th June 1995
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Alexander E. Andreev, Andrea E. F. Clementi, Jose Rolim#### Optimal Bounds for the Approximation of Boolean Functions and Some Applications

Alexander E. Andreev, Andrea E. F. Clementi, Paolo Penna, Jose' D. P. Rolim

We address the problem of organizing a set $T$ of shared data into

the memory modules of a Distributed Memory Machine (DMM) in order

to minimize memory access conflicts (i.e. memory contention)

during read operations.

Previous solutions for this problem can be found as fundamental ...
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Alexander E. Andreev, J. L. Baskakov, Andrea E. F. Clementi, Jose' D. P. Rolim

We show the following Reduction Lemma: any

$\epsilon$-biased sample space with respect to (Boolean) linear

tests is also $2\epsilon$-biased with respect to

any system of independent linear tests. Combining this result with

the previous constructions of $\epsilon$-biased sample space with

respect to linear tests, we obtain the first efficient

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Alexander E. Andreev, Andrea E. F. Clementi, Jose' D.P. Rolim and Trevisan

We show how to simulate any BPP algorithm in polynomial time

using a weak random source of min-entropy $r^{\gamma}$

for any $\gamma >0$.

This follows from a more general result about {\em sampling\/}

with weak random sources.

Our result matches an information-theoretic lower bound ...
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Alexander E. Andreev, Andrea E. F. Clementi, Jose' D. P. Rolim

We present the first worst-case hardness conditions

on the circuit complexity of EXP functions which are

sufficient to obtain P=BPP. In particular, we show that

from such hardness conditions it is possible to construct

quick Hitting Sets Generators with logarithmic prize.

...
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Alexander E. Andreev, Andrea E. F. Clementi, Jose' D. P. Rolim

The efficient construction of Hitting Sets for non trivial classes

of boolean functions is a fundamental problem in the theory

of derandomization. Our paper presents a new method to efficiently

construct Hitting Sets for the class of systems of boolean linear

functions. Systems of boolean linear functions ...
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Alexander E. Andreev, Andrea E. F. Clementi, Jose' D. P. Rolim

We show that hitting sets can derandomize any BPP-algorithm.

This gives a positive answer to a fundamental open question in

probabilistic algorithms. More precisely, we present a polynomial

time deterministic algorithm which uses any given hitting set

to approximate the fractions of 1's in the ...
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Alexander E. Andreev, Andrea E. F. Clementi, Jose Rolim

We prove an optimal bound on the Shannon function

$L(n,m,\epsilon)$ which describes the trade-off between the

circuit-size complexity and the degree of approximation; that is

$$L(n,m,\epsilon)\ =\

\Theta\left(\frac{m\epsilon^2}{\log(2 + m\epsilon^2)}\right)+O(n).$$

Our bound applies to any partial boolean function

and any ...
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