Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Spallitta, Giuseppe"'
This paper builds on top of a paper we have published very recently, in which we have proposed a novel approach to prime factorization (PF) by quantum annealing, where 8,219,999=32,749x251 was the highest prime product we were able to factorize -- wh
Externí odkaz:
http://arxiv.org/abs/2406.07732
Decision diagrams (DDs) are powerful tools to represent effectively propositional formulas, which are largely used in many domains, in particular in formal verification and in knowledge compilation. Some forms of DDs (e.g., OBDDs, SDDs) are canonical
Externí odkaz:
http://arxiv.org/abs/2404.16455
This paper investigates novel techniques to solve prime factorization by quantum annealing (QA). Our contribution is twofold. First, we present a novel and very compact modular encoding of a binary multiplier circuit into the Pegasus architecture of
Externí odkaz:
http://arxiv.org/abs/2310.17574
A basic algorithm for enumerating disjoint propositional models (disjoint AllSAT) is based on adding blocking clauses incrementally, ruling out previously found models. On the one hand, blocking clauses have the potential to reduce the number of gene
Externí odkaz:
http://arxiv.org/abs/2306.00461
Modern SAT and SMT solvers are designed to handle problems expressed in Conjunctive Normal Form (CNF) so that non-CNF problems must be CNF-ized upfront, typically by using variants of either Tseitin or Plaisted and Greenbaum transformations. When pas
Externí odkaz:
http://arxiv.org/abs/2303.14971
Autor:
Spallitta, Giuseppe, Masina, Gabriele, Morettin, Paolo, Passerini, Andrea, Sebastiani, Roberto
The development of efficient exact and approximate algorithms for probabilistic inference is a long-standing goal of artificial intelligence research. Whereas substantial progress has been made in dealing with purely discrete or purely continuous dom
Externí odkaz:
http://arxiv.org/abs/2302.06188
Autor:
Spallitta, Giuseppe, Masina, Gabriele, Morettin, Paolo, Passerini, Andrea, Sebastiani, Roberto
Weighted Model Integration (WMI) is a popular formalism aimed at unifying approaches for probabilistic inference in hybrid domains, involving logical and algebraic constraints. Despite a considerable amount of recent work, allowing WMI algorithms to
Externí odkaz:
http://arxiv.org/abs/2206.13856
Autor:
Spallitta, Giuseppe, Masina, Gabriele, Morettin, Paolo, Passerini, Andrea, Sebastiani, Roberto
Publikováno v:
In Artificial Intelligence March 2024 328
Autor:
Ding, Jingwen1 (AUTHOR), Spallitta, Giuseppe1 (AUTHOR), Sebastiani, Roberto1 (AUTHOR) roberto.sebastiani@unitn.it
Publikováno v:
Scientific Reports. 2/12/2024, Vol. 14 Issue 1, p1-14. 14p.
Publikováno v:
Frontiers in Computer Science; 2024, p1-9, 9p