Add to ORKGBefore we study the derandomization of randomized algorithms, we will need some algorithms to derandomize. Thus in this section, we present a number of examples of randomized algorithms, as well as develop the complexity-theoretic framework and basic tools for studying random-ized algorithms. 2.1 Polynomial Identity Testing In this section, we give a randomized algorithm to solve the following computational problem
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
This dissertation explores the multifaceted interplay between efficient computation and probability ...
Does derandomization of probabilistic algorithms become easier when the number of “bad” random input...
I returned, and saw under the sun, that the race is not to the swift, nor the battle to the strong, ...
Noam Nisan constructed pseudo random number generators which convert O(S log R) truly random bits to...
We present a Monte Carlo algorithm for testing multivariate polynomial identities over any field usi...
AbstractResearch conducted over the past fifteen years has amply demonstrated the advantages of algo...
The isolation lemma of Mulmuley et al [MVV87] is an important tool in the design of randomized algor...
In recent years, many probabilistic algorithms (i.e., algorithms that can toss coins) that run in po...
In recent years, many probabilistic algorithms (i.e., algorithms that can toss coins) that run in po...
Abstract. We describe an efficient randomized algorithm to test if a given binary function is a low-...
We show that lower bounds for explicit constant-variate polynomials over fields of characteristic p ...
Abstract Motivated by questions about secure multi-party compu-tation, we introduce and study a new ...
Randomization is of paramount importance in practical applications and randomized algorithms are us...
We describe an efficient randomized algorithm to test if a given binary function f : f0; 1g ! f0...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
This dissertation explores the multifaceted interplay between efficient computation and probability ...
Does derandomization of probabilistic algorithms become easier when the number of “bad” random input...
I returned, and saw under the sun, that the race is not to the swift, nor the battle to the strong, ...
Noam Nisan constructed pseudo random number generators which convert O(S log R) truly random bits to...
We present a Monte Carlo algorithm for testing multivariate polynomial identities over any field usi...
AbstractResearch conducted over the past fifteen years has amply demonstrated the advantages of algo...
The isolation lemma of Mulmuley et al [MVV87] is an important tool in the design of randomized algor...
In recent years, many probabilistic algorithms (i.e., algorithms that can toss coins) that run in po...
In recent years, many probabilistic algorithms (i.e., algorithms that can toss coins) that run in po...
Abstract. We describe an efficient randomized algorithm to test if a given binary function is a low-...
We show that lower bounds for explicit constant-variate polynomials over fields of characteristic p ...
Abstract Motivated by questions about secure multi-party compu-tation, we introduce and study a new ...
Randomization is of paramount importance in practical applications and randomized algorithms are us...
We describe an efficient randomized algorithm to test if a given binary function f : f0; 1g ! f0...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
This dissertation explores the multifaceted interplay between efficient computation and probability ...
Does derandomization of probabilistic algorithms become easier when the number of “bad” random input...