Randomness extractors are efficient algorithms which convert weak random sources into nearly perfect ones. While such purification of randomness was the original motivation for constructing extractors, these constructions turn out to have strong pseudorandom properties which found applications in diverse areas of computer science and combinatorics. We will highlight some of the applications, as well as recent constructions achieving near-optimal extraction
We deal with the problem of extracting as much randomness as possible from a defective random source...
© International Association for Cryptologic Research 2020. We revisit the well-studied problem of ex...
We introduce a new approach to constructing extractors. Extractors are algorithms that transform a “...
Randomness is crucial to computer science, both in theory and applications. In complexity theory, ra...
Randomness is crucial to computer science, both in theory and applications. In complexity theory, ra...
Randomness is crucial to computer science, both in theory and applications. In complexity theory, ra...
Randomness extractors, which extract high quality (almost-uniform) random bits from biased random so...
textThe use of randomized algorithms and protocols is ubiquitous in computer science. Randomized sol...
textThe use of randomized algorithms and protocols is ubiquitous in computer science. Randomized sol...
Randomness extractors are functions that extract almost-uniform bits from sources of biased and corr...
In this thesis we study the problem of extracting almost truly random bits from imperfect sources of...
In this thesis we study the problem of extracting almost truly random bits from imperfect sources of...
Linear transformations have many applications in information theory, like data compression and error...
Linear transformations have many applications in information theory, like data compression and error...
We introduce a new approach to construct extractors --- combinatorial objects akin to expander graph...
We deal with the problem of extracting as much randomness as possible from a defective random source...
© International Association for Cryptologic Research 2020. We revisit the well-studied problem of ex...
We introduce a new approach to constructing extractors. Extractors are algorithms that transform a “...
Randomness is crucial to computer science, both in theory and applications. In complexity theory, ra...
Randomness is crucial to computer science, both in theory and applications. In complexity theory, ra...
Randomness is crucial to computer science, both in theory and applications. In complexity theory, ra...
Randomness extractors, which extract high quality (almost-uniform) random bits from biased random so...
textThe use of randomized algorithms and protocols is ubiquitous in computer science. Randomized sol...
textThe use of randomized algorithms and protocols is ubiquitous in computer science. Randomized sol...
Randomness extractors are functions that extract almost-uniform bits from sources of biased and corr...
In this thesis we study the problem of extracting almost truly random bits from imperfect sources of...
In this thesis we study the problem of extracting almost truly random bits from imperfect sources of...
Linear transformations have many applications in information theory, like data compression and error...
Linear transformations have many applications in information theory, like data compression and error...
We introduce a new approach to construct extractors --- combinatorial objects akin to expander graph...
We deal with the problem of extracting as much randomness as possible from a defective random source...
© International Association for Cryptologic Research 2020. We revisit the well-studied problem of ex...
We introduce a new approach to constructing extractors. Extractors are algorithms that transform a “...