Constraint Programming is an attractive approach for solving AI planning problems by modelling them as Constraint Satisfaction Problems (CSPs). However, formulating effective cons...
Andrea Rendl, Ian Miguel, Ian P. Gent, Peter Grego...
Recent work has shown the value of using unsatisfiable cores to guide maximum satisfiability algorithms (Max-SAT) running on industrial instances [5,9,10,11]. We take this concep...
Over the last 25+ years, the software community has been searching for the best models for estimating variables of interest (e.g., cost, defects, and fault proneness). However, li...
Discriminative training has been a leading factor for improving automatic speech recognition (ASR) performance over the last decade. The traditional discriminative training, howev...
It has been widely observed that there is no “dominant” SAT solver; instead, different solvers perform best on different instances. Rather than following the traditional appr...
Lin Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton...