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: "an extremal inequality for long markov chains"
  Abstract: Let $X,Y$ be jointly Gaussian vectors, and consider random variables $U,V$ that satisfy the Markov constraint $U-X-Y-V$. We prove an extremal inequality relating the mutual informations between all ${4 \choose 2}$ pairs of random variables from the set $(U,X,Y,V)$. As a first application, we show that the rate region for the two-encoder quadratic Gaussian source coding problem follows as an immediate corollary of the the extremal inequality. In a second application, we establish the rate region for a vector-Gaussian source coding problem where L\"{o}wner-John ellipsoids are approximated based on rate-constrained descriptions of the data.

Connected through hyperedge HE-1 (induced by source paper "extracting robust and accurate features via a robust information bottleneck"):
  with members:
    - "certified adversarial robustness via randomized smoothing"
    - "unifying the brascamp lieb inequality and the entropy power inequality"
    - "where is the information in a deep neural network"
    - "a family of bayesian cram er rao bounds and consequences for log concave priors"
    - "theoretically principled trade off between robustness and accuracy"
    - "provably robust deep learning via adversarially trained smoothed classifiers"
    - "does learning require memorization a short tale about a long tail"
    - "defending against whitebox adversarial attacks via randomized discretization"

Connected through hyperedge HE-2 (induced by source paper "unifying the brascamp lieb inequality and the entropy power inequality"):
  with members:
    - "strong data processing inequalities for channels and bayesian networks"
    - "yet another proof of the entropy power inequality"
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "superposition coding is almost always optimal for the poisson broadcast channel"
    - "information theoretic proofs of entropy power inequalities"

Connected through hyperedge HE-3 (induced by source paper "vector gaussian ceo problem under logarithmic loss and applications"):
  with members:
    - "vector gaussian ceo problem under logarithmic loss"
    - "chaining mutual information and tightening generalization bounds"
    - "on the universality of the logistic loss function"
    - "minimax learning for remote prediction"
    - "information theoretic analysis of generalization capability of learning algorithms"
    - "distributed information bottleneck method for discrete and gaussian sources"
    - "universality of logarithmic loss in lossy compression"
    - "a generalization of blahut arimoto algorithm to compute rate distortion regions of multiterminal source coding under logarithmic loss"

Connected through hyperedge HE-4 (induced by source paper "information theoretic perspectives on brascamp lieb inequality and its reverse"):
  with members:
    - "arimoto r enyi conditional entropy and bayesian m ary hypothesis testing"
    - "strengthening the entropy power inequality"
    - "algorithmic and optimization aspects of brascamp lieb inequalities via operator scaling"
    - "brascamp lieb inequality and its reverse an information theoretic view"
    - "converses for distributed estimation via strong data processing inequalities"
    - "secret key generation with one communicator and a one shot converse via hypercontractivity"
    - "on non interactive simulation of joint distributions"
    - "a note on the strong data processing inequalities in bayesian networks"

Connected through hyperedge HE-5 (induced by source paper "strengthening the entropy power inequality"):
  with members:
    - "forward and reverse entropy power inequalities in convex geometry"
    - "entropy bounds on abelian groups and the ruzsa divergence"
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "justification of logarithmic loss via the benefit of side information"
    - "dissipation of information in channels with input constraints"
    - "a strengthened entropy power inequality for log concave densities"
    - "strong data processing inequalities and phi sobolev inequalities for discrete channels"
    - "sumset and inverse sumset inequalities for differential entropy and mutual information"

Connected through hyperedge HE-6 (induced by source paper "brascamp lieb inequality and its reverse an information theoretic view"):
  with members:
    - "information theoretic perspectives on brascamp lieb inequality and its reverse"
    - "converses for distributed estimation via strong data processing inequalities"
    - "secret key generation with one communicator and a one shot converse via hypercontractivity"
    - "a note on the strong data processing inequalities in bayesian networks"
    - "communication lower bounds for statistical estimation problems via a distributed data processing inequality"
    - "information theoretic applications of the logarithmic probability comparison bound"
    - "key capacity for product sources with application to stationary gaussian processes"
    - "wyner s common information generalizations and a new lossy source coding interpretation"

Connected through hyperedge HE-7 (induced by source paper "gaussian secure source coding and wyner s common information"):
  with members:
    - "secure coordination with a two sided helper"
    - "the lossy common information of correlated sources"
    - "wyner s common information generalizations and a new lossy source coding interpretation"
    - "a bit of secrecy for gaussian source compression"
    - "optimal equivocation in secrecy systems a special case of distortion based characterization"
    - "on secure source coding with side information at the encoder"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"

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)