MaxSAT solving is becoming a competitive generic approach for solving combinatorial
optimization problems, partly due to the development of new solving techniques that have …

Recent work proposed a toolkit PySAT aiming at fast and easy prototy** with propositional
satisfiability (SAT) oracles in Python, which enabled one to exploit the power of the original …

This paper presents open-wbo, a new MaxSAT solver. open-wbo has two main features.
First, it is an open-source solver that can be easily modified and extended. Most MaxSAT …

Tree ensembles (TEs) denote a prevalent machine learning model that do not offer
guarantees of interpretability, that represent a challenge from the perspective of explainable …

Abstract Maximum Satisfiability (MaxSAT) is an optimization version of SAT, and many real
world applications can be naturally encoded as such. Solving MaxSAT is an important …

In the last couple of decades, developments in SAT-based optimization have led to highly
efficient maximum satisfiability (MaxSAT) solvers, but in contrast to the SAT solvers on which …

Many industrial optimization problems can be translated to MaxSAT. Although the general
problem is NP hard, like SAT, many practical problems may be solved using modern …

Maximum satisfiability (MaxSAT) is an optimization version of SAT that is solved by finding
an optimal truth assignment instead of just a satisfying one. In MaxSAT the objective function …

Maximum Satisfiability (MaxSAT) is a well-known optimization variant of propositional
Satisfiability (SAT). Motivated by a growing number of practical applications, recent years …

This paper proposes a technique for automatically learning semantic malware signatures for
Android from very few samples of a malware family. The key idea underlying our technique …