The focus of this monograph is the question of quantified derandomization. Does derandomization of probabilistic algorithms become easier if we only want to derandomize algorithms that err with extremely small probability? How small does this probability need to be in order for the problem's complexity to be affected?
In this comprehensive survey of the topic, the author describes the body of knowledge accumulated since the question was first raised in 2014, focusing on the following directions: 1) Hardness vs "quantified" randomness; 2) Improving on the brute-force algorithm for quantified derandomization implies breakthrough circuit lower bounds; 3) Unconditional algorithms for quantified derandomization of low-depth circuits and formulas; 4) Arithmetic quantified derandomization; 5) Limitations of certain black-box techniques and pseudoentropy.
Written for researchers, this monograph provides the readers with a concise overview of all known results, but the author also shows several results that are either new or are strengthenings of others. The author also offers a host of concrete challenges and open questions surrounding quantified derandomization.
The focus of this monograph is the question of quantified derandomization. Does derandomization of probabilistic algorithms become easier if we only want to derandomize algorithms that err with extremely small probability? How small does this probability need to be in order for the problem's complexity to be affected?
In this comprehensive survey of the topic, the author describes the body of knowledge accumulated since the question was first raised in 2014, focusing on the following directions: 1) Hardness vs "quantified" randomness; 2) Improving on the brute-force algorithm for quantified derandomization implies breakthrough circuit lower bounds; 3) Unconditional algorithms for quantified derandomization of low-depth circuits and formulas; 4) Arithmetic quantified derandomization; 5) Limitations of certain black-box techniques and pseudoentropy.
Written for researchers, this monograph provides the readers with a concise overview of all known results, but the author also shows several results that are either new or are strengthenings of others. The author also offers a host of concrete challenges and open questions surrounding quantified derandomization.
This volume covers a wide range of topics that fall under the 'philosophy of quantifiers', a philosophy that spans across multiple areas such as logic, metaphysics, epistemology and even the history...
Quantifiers: Logics, Models and Computation is the first concentrated effort to give a systematic presentation of the main research results on the subject, since the modern concept was ...
Göran Grimvall is determined to help mere mortals understand how scientists get to the kernel of perplexing problems. Entertaining and enlightening, his latest book uses examples from sports,...
What is at stake socially, culturally, politically, and economically when we routinely use technology to gather information about our bodies and environments? Today anyone can purchase technology...
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