Suppose a language L can be decided by a bounded-error randomized algorithm that runs in space S and time n * poly(S). We give a randomized algorithm for L that still runs in space O(S) and time n * poly(S) that uses only O(S) random bits; our algorithm has a low failure probability on all but a negligible fraction of inputs of each length. As an immediate corollary, there is a deterministic algorithm for L that runs in space O(S) and succeeds on all but a negligible fraction of inputs of each length. We also give several other complexity-theoretic applications of our technique
Borodin, Cook, and Pippenger (Inform. and Control 58 (1983), 96–114) proved that both probabilistic ...
We prove the first time-space lower bound tradeoffs for randomized computation of decision problems....
Abstract. Many theorems about Kolmogorov complexity rely on exis-tence of combinatorial objects with...
AbstractWe show that any randomized algorithm that runs in spaceSand timeTand uses poly(S) random bi...
Existing proofs that deduce BPL = ? from circuit lower bounds convert randomized algorithms into det...
To what extent is randomness necessary for efficient computation? We study the problem of determinis...
Parallel time and space are perhaps the two most fundamental resources in computation. They appear t...
AbstractWe prove that if BPP≠EXP, then every problem in BPP can be solved deterministically in subex...
Noam Nisan constructed pseudo random number generators which convert O(S log R) truly random bits to...
Investigating the complexity of randomized space-bounded machines that are allowed to make multiple ...
This dissertation explores the multifaceted interplay between efficient computation and probability ...
This paper initiates the study of deterministic ampli-fication of space-bounded probabilistic algori...
Abstract Various efforts ([3, 5, 6, 9]) have been made in recentyears to derandomize probabilistic a...
Does derandomization of probabilistic algorithms become easier when the number of “bad” random input...
We show that popular hardness conjectures about problems from the field of fine-grained complexity t...
Borodin, Cook, and Pippenger (Inform. and Control 58 (1983), 96–114) proved that both probabilistic ...
We prove the first time-space lower bound tradeoffs for randomized computation of decision problems....
Abstract. Many theorems about Kolmogorov complexity rely on exis-tence of combinatorial objects with...
AbstractWe show that any randomized algorithm that runs in spaceSand timeTand uses poly(S) random bi...
Existing proofs that deduce BPL = ? from circuit lower bounds convert randomized algorithms into det...
To what extent is randomness necessary for efficient computation? We study the problem of determinis...
Parallel time and space are perhaps the two most fundamental resources in computation. They appear t...
AbstractWe prove that if BPP≠EXP, then every problem in BPP can be solved deterministically in subex...
Noam Nisan constructed pseudo random number generators which convert O(S log R) truly random bits to...
Investigating the complexity of randomized space-bounded machines that are allowed to make multiple ...
This dissertation explores the multifaceted interplay between efficient computation and probability ...
This paper initiates the study of deterministic ampli-fication of space-bounded probabilistic algori...
Abstract Various efforts ([3, 5, 6, 9]) have been made in recentyears to derandomize probabilistic a...
Does derandomization of probabilistic algorithms become easier when the number of “bad” random input...
We show that popular hardness conjectures about problems from the field of fine-grained complexity t...
Borodin, Cook, and Pippenger (Inform. and Control 58 (1983), 96–114) proved that both probabilistic ...
We prove the first time-space lower bound tradeoffs for randomized computation of decision problems....
Abstract. Many theorems about Kolmogorov complexity rely on exis-tence of combinatorial objects with...