Learning efficient representations of complex constraints for scalable optimization
PolyFormer, a PIML framework that learns compact polytopic representations of the geometry induced by complex constraints, is introduced, establishing learned geometric constraint representations as an effective and scalable route to prescriptive optimization under diverse forms of constraint complexity.
Yi-Lin Wen, Yi Guo, Bo Zhao et al.
· 0 citations