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William Bradley

dblp:06/9366 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2024
0000-0003-2505-6898ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Coding theory · 92% Mathematical optimization · 8%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory
error-correcting codes		 0.112012
Reweighted LP Decoding for LDPC Codes · IEEE Trans. Inf. Theory 2012
Coding theory › error-correcting codes
LDPC codes		 0.112012
Reweighted LP Decoding for LDPC Codes · IEEE Trans. Inf. Theory 2012
Coding theory › error-correcting codes › LDPC codes
linear programming decoding		 0.112012
Reweighted LP Decoding for LDPC Codes · IEEE Trans. Inf. Theory 2012
Coding theory › error-correcting codes
decoding		 0.012012
Reweighted LP Decoding for LDPC Codes · IEEE Trans. Inf. Theory 2012
Mathematical optimization
linear programming		 0.012012
Reweighted LP Decoding for LDPC Codes · IEEE Trans. Inf. Theory 2012

Methods — techniques the papers use, named apart from their topics

threshold analysis · 0.1reweighting · 0.1linear programming · 0.1
YearPublicationVenuePosition
2024 Enabling global interpolation, derivative estimation and model identification from sparse multi-experiment time series data via neural ODEs
William Bradley, Ron Volkovinsky, Fani Boukouvala
 Eng. Appl. Artif. Intell.1
2012 Reweighted LP Decoding for LDPC Codes
abstract
We introduce a novel algorithm for decoding binary linear codes by linear programming (LP). We build on the LP decoding algorithm of Feldman and introduce a postprocessing step that solves a second linear program that reweights the objective function based on the outcome of the original LP decoder output. Our analysis shows that for some LDPC ensembles we can improve the provable threshold guarantees compared to standard LP decoding. We also show significant empirical performance gains for the reweighted LP decoding algorithm with very small additional computational complexity.
M. Amin Khajehnejad, Alexandros G. Dimakis, Babak Hassibi, Benjamin Vigoda, William Bradley
 IEEE Trans. Inf. Theory5