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Trung Van Pham

dblp:204/3470 · DBLP profile ↗
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3ranked-venue papers
2as first author
1since 2021 · last 2022
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorTheory 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
Logic in computer science · 54% Computational complexity · 46%

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

TopicWeightPapersLastEvidence papers
Computational complexity
constraint satisfaction
0.312017
The equivalence of two dichotomy conjectures for infinite domain constraint satisfaction problems · LICS 2017
Logic in computer science › model theory
homogeneous structures
0.312017
The equivalence of two dichotomy conjectures for infinite domain constraint satisfaction problems · LICS 2017
Computational complexity › constraint satisfaction
infinite-domain constraint satisfaction
0.312017
The equivalence of two dichotomy conjectures for infinite domain constraint satisfaction problems · LICS 2017
Logic in computer science
model theory
0.312017
The equivalence of two dichotomy conjectures for infinite domain constraint satisfaction problems · LICS 2017
Logic in computer science
universal algebra
0.112017
The equivalence of two dichotomy conjectures for infinite domain constraint satisfaction problems · LICS 2017

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

ramsey property · 0.3monoid theory · 0.3model-complete core · 0.3
YearPublicationVenuePosition
2022 Improvement in design and training of feature pyramid network for contour refinement
Trung Van Pham, Yves Lucas, Sylvie Treuillet, Laurent Debraux
Pattern Recognit. Lett.1
2020 Object Contour Refinement Using Instance Segmentation in Dental Images
Trung Van Pham, Yves Lucas, Sylvie Treuillet, Laurent Debraux
ACIVS1
2017 The equivalence of two dichotomy conjectures for infinite domain constraint satisfaction problems
abstract
There exist two conjectures for constraint satisfaction problems (CSPs) of reducts of finitely bounded homogeneous structures: the first one states that tractability of the CSP of such a structure is, when the structure is a model-complete core, equivalent to its polymorphism clone satisfying a certain non-trivial linear identity modulo outer embeddings. The second conjecture, challenging the approach via model-complete cores by reflections, states that tractability is equivalent to the linear identities (without outer embeddings) satisfied by its polymorphisms clone, together with the natural uniformity on it, being non-trivial. We prove that the identities satisfied in the polymorphism clone of a structure allow for conclusions about the orbit growth of its automorphism group, and apply this to show that the two conjectures are equivalent. We contrast this with a counterexample showing that ω-categoricity alone is insufficient to imply the equivalence of the two conditions above in a model-complete core. Taking a different approach, we then show how the Ramsey property of a homogeneous structure can be utilized for obtaining a similar equivalence under different conditions. We then prove that any polymorphism of sufficiently large arity which is totally symmetric modulo outer embeddings of a finitely bounded structure can be turned into a non-trivial system of linear identities, and obtain non-trivial linear identities for all tractable cases of reducts of the rational order, the random graph, and the random poset. Finally, we provide a new and short proof, in the language of monoids, of the theorem stating that every ω-categorical structure is homomorphically equivalent to a model-complete core.
Libor Barto, Michael Kompatscher, Miroslav Olsák, Trung Van Pham, Michael Pinsker
LICS4