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: "evaluation of marton s inner bound for the general broadcast channel"
  Abstract: The best known inner bound on the two-receiver general broadcast channel is due to Marton. However this region is not computable (except in certain special cases) as no bounds on the cardinality of its auxiliary random variables exist. Nor is it even clear that the inner bound is a closed set. The main obstacle in proving cardinality bounds is the fact that the traditional use of the Caratheodory theorem, the main known tool for proving cardinality bounds, does not yield a finite cardinality result. One of the main contributions of this paper is the introduction of a new tool based on an identity that relates the second derivative of the Shannon entropy of a discrete random variable (under a certain perturbation) to the corresponding Fisher information. In order to go beyond the traditional Caratheodory type arguments, we identify certain properties that the auxiliary random variables corresponding to the extreme points of the inner bound need to satisfy. These properties are then used to establish cardinality bounds on the auxiliary random variables of the inner bound, thereby proving the computability of the region, and its closedness. Lastly, we establish a conjecture of Nair and Zizhou that Marton's inner bound and the recent outer bound of Nair and El Gamal do not match in general.

Connected through hyperedge HE-1 (induced by source paper "on the direction of discrimination an information theoretic analysis of disparate impact in machine learning"):
  with members:
    - "hypothesis testing in the high privacy limit"
    - "iterative orthogonal feature projection for diagnosing bias in black box models"
    - "discrimination in online ad delivery"
    - "on maximal correlation hypercontractivity and the data processing inequality studied by erkip and cover"
    - "evaluation of marton s inner bound for the general broadcast channel"

Connected through hyperedge HE-2 (induced by source paper "strong secrecy for cooperative broadcast channels"):
  with members:
    - "broadcast channels with privacy leakage constraints"
    - "fourier motzkin elimination software for information theoretic inequalities"
    - "the likelihood encoder for lossy compression"
    - "duality of a source coding problem and the semi deterministic broadcast channel with rate limited cooperation"
    - "semantic security capacity for wiretap channels of type ii"
    - "secrecy capacity region of some classes of wiretap broadcast channels"
    - "on state dependent broadcast channels with cooperation"
    - "the henchman problem measuring secrecy by the minimum distortion in a list"

Connected through hyperedge HE-3 (induced by source paper "duality of a source coding problem and the semi deterministic broadcast channel with rate limited cooperation"):
  with members:
    - "empirical coordination in a triangular multiterminal network"
    - "successive refinement with decoder cooperation and its channel coding duals"
    - "mac with action dependent state information at one encoder"
    - "the state dependent semideterministic broadcast channel"
    - "multiterminal source coding under logarithmic loss"
    - "the compound multiple access channel with partially cooperating encoders"
    - "compound multiple access channels with partial cooperation"
    - "evaluation of marton s inner bound for the general broadcast channel"

Connected through hyperedge HE-4 (induced by source paper "distributed information theoretic biclustering"):
  with members:
    - "which boolean functions are most informative"
    - "demystifying information theoretic clustering"
    - "multiterminal source coding under logarithmic loss"
    - "evaluation of marton s inner bound for the general broadcast channel"

Connected through hyperedge HE-5 (induced by source paper "polar codes for broadcast channels"):
  with members:
    - "achieving marton s region for broadcast channels using polar codes"
    - "a comparison of superposition coding schemes"
    - "polar codes for the two user multiple access channel"
    - "polar codes for q ary channels q 2 r"
    - "how to construct polar codes"
    - "achieving the secrecy capacity of wiretap channels using polar codes"
    - "multilevel polarization of polar codes over arbitrary discrete memoryless channels"
    - "channel polarization on q ary discrete memoryless channels by arbitrary kernels"

Connected through hyperedge HE-6 (induced by source paper "bounds between contraction coefficients"):
  with members:
    - "comparison of channels criteria for domination by a symmetric channel"
    - "f divergence inequalities"
    - "strong data processing inequalities for input constrained additive noise channels"
    - "information extraction under privacy constraints"
    - "tight bounds for symmetric divergence measures and a new inequality relating f divergences"
    - "dissipation of information in channels with input constraints"
    - "strong data processing inequalities and phi sobolev inequalities for discrete channels"
    - "linear information coupling problems"

Connected through hyperedge HE-7 (induced by source paper "outer bounds on the admissible source region for broadcast channels with correlated sources"):
  with members:
    - "a note on outer bounds for broadcast channel"
    - "the capacity region of classes of product broadcast channels"
    - "optimality and approximate optimality of source channel separation in networks"
    - "evaluation of marton s inner bound for the general broadcast channel"
    - "correlated sources over broadcast channels"
    - "outer bounds on the admissible source region for broadcast channels with dependent sources"
    - "comments on broadcast channels with arbitrarily correlated sources"
    - "approximate characterizations for the gaussian source broadcast distortion region"

Connected through hyperedge HE-8 (induced by source paper "on the duality of additivity and tensorization"):
  with members:
    - "on non interactive simulation of joint distributions"
    - "key capacity with limited one way communication for product sources"
    - "an exploration of the role of principal inertia components in information theory"
    - "key capacity for product sources with application to stationary gaussian processes"
    - "on maximal correlation hypercontractivity and the data processing inequality studied by erkip and cover"
    - "a new data processing inequality and its applications in distributed source and channel coding"
    - "evaluation of marton s inner bound for the general broadcast channel"

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)