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: "equivalence of two proof techniques for non shannon type inequalities"
  Abstract: We compare two different techniques for proving non-Shannon-type information inequalities. The first one is the original Zhang-Yeung's method, commonly referred to as the copy/pasting lemma/trick. The copy lemma was used to derive the first conditional and unconditional non-Shannon-type inequalities. The second technique first appeared in Makarychev et al paper [7] and is based on a coding lemma from Ahlswede and K\"orner works. We first emphasize the importance of balanced inequalities and provide a simpler proof of a theorem of Chan's for the case of Shannon-type inequalities. We compare the power of various proof systems based on a single technique.

Connected through hyperedge HE-1 (induced by source paper "how to use undiscovered information inequalities direct applications of the copy lemma"):
  with members:
    - "partition symmetrical entropy functions"
    - "entropy region and convolution"
    - "non shannon information inequalities in four random variables"
    - "improved upper bounds for the information rates of the secret sharing schemes induced by the vamos matroid"

Connected through hyperedge HE-2 (induced by source paper "mapping the region of entropic vectors with support enumeration information geometry"):
  with members:
    - "entropy region and convolution"
    - "finite p groups entropy vectors and the ingleton inequality for nilpotent groups"
    - "non shannon information inequalities in four random variables"
    - "linear rank inequalities on five or more variables"
    - "mission impossible computing the network coding capacity region"
    - "a projection method for derivation of non shannon type information inequalities"
    - "entropy vectors and network codes"
    - "dualities between entropy functions and network codes"

Connected through hyperedge HE-3 (induced by source paper "entropy region and convolution"):
  with members:
    - "conditional information inequalities for entropic and almost entropic points"
    - "on the ingleton violations in finite groups"
    - "on the non robustness of essentially conditional information inequalities"
    - "on essentially conditional information inequalities"
    - "non shannon information inequalities in four random variables"
    - "graph theoretical constructions for graph entropy and network coding based communications"

Connected through hyperedge HE-4 (induced by source paper "using multiobjective optimization to map the entropy region of four random variables"):
  with members:
    - "non shannon information inequalities in four random variables"

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)