Genetic algorithms are a robust adaptive optimization technique based on a biological paradigm. They perform efficient search on poorly-defined spaces by maintaining an ordered po...
Some of the most successful algorithms for satisfiability, such as Walksat, are based on random walks. Similarly, local search algorithms for solving constraint optimization proble...
Constraint programming uses enumeration and search tree pruning to solve combinatorial optimization problems. In order to speed up this solution process, we investigate the use of...
This paper suggests a method for multiclass learning with many classes by simultaneously learning shared characteristics common to the classes, and predictors for the classes in t...
Yonatan Amit, Michael Fink 0002, Nathan Srebro, Sh...
We describe some new propagators for breaking symmetries in constraint satisfaction problems. We also introduce symmetry breaking constraints to deal with symmetries acting simulta...