Fine-grained reductions from approximate counting to decision
- Submitting institution
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University of Bristol
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 208378814
- Type
- E - Conference contribution
- DOI
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10.1145/3188745.3188920
- Title of conference / published proceedings
- Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing
- First page
- 281
- Volume
- -
- Issue
- -
- ISSN
- 0737-8017
- Open access status
- Technical exception
- Month of publication
- June
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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1
- Research group(s)
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D - Fundamentals of Computing
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper appeared at STOC. Many counting problems have an associated (easier) decision problem; for example, counting satisfying assignments corresponds to checking satisfiability. We show that often, algorithms for decision problems can be bootstrapped into approximate algorithms for counting problems *with essentially the same running time*, in a "black box" fashion which ignores most of the problem's structure. These results have since been substantially generalised by the authors together with Meeks, and have inspired analogous work into parity problems (Abboud etc. ICALP 2020). The paper was a major factor in both authors getting permanent positions at Bristol and ITU.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -