as regards of supper efficiency models which increased thediscrimination power of the standard dea models, still infeasibility mayoccure. in literature there exists some models overcome this difficulty.in this paper a new procedure has been mooted in order to remove thisshortcoming in a way that both input savings and output surplus arebeing considered. this procedure deals with nonradial chang...

In recent years, powered by the learned discriminative representation via graph neural network (GNN) models, deep matching methods have made great progresses in task of semantic features. However, these usually rely on heuristically generated patterns, which may introduce unreliable relationships to hurt performance. this paper, we propose a joint learning and network, named GLAM, explore relia...