human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "another look at expurgated bounds and their statistical mechanical interpretation"
  Abstract: We revisit the derivation of expurgated error exponents using a method of type class enumeration, which is inspired by statistical-mechanical methods, and which has already been used in the derivation of random coding exponents in several other scenarios. We compare our version of the expurgated bound to both the one by Gallager and the one by Csiszar, Korner and Marton (CKM). For expurgated ensembles of fixed composition codes over finite alphabets, our basic expurgated bound coincides with the CKM expurgated bound, which is in general tighter than Gallager's bound, but with equality for the optimum type class of codewords. Our method, however, extends beyond fixed composition codes and beyond finite alphabets, where it is natural to impose input constraints (e.g., power limitation). In such cases, the CKM expurgated bound may not apply directly, and our bound is in general tighter than Gallager's bound. In addition, while both the CKM and the Gallager expurgated bounds are based on Bhattacharyya bound for bounding the pairwise error probabilities, our bound allows the more general Chernoff distance measure, thus giving rise to additional improvement using the Chernoff parameter as a degree of freedom to be optimized.

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)