2 papers
cs.LG2025
Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic Models
Marcio Nicolau, Anderson R. Tavares, Zhiwei Zhang +4
Computational learning theory states that many classes of boolean formulas are learnable in polynomial time. This paper addresses the understudied subject of how, in practice, such…
cs.LO2025
Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization
Zhiwei Zhang, Samy Wu Fung, Anastasios Kyrillidis +2
The Boolean satisfiability (SAT) problem lies at the core of many applications in combinatorial optimization, software verification, cryptography, and machine learning. While state…