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: "the most informative boolean function conjecture holds for high noise"
  Abstract: We prove the "Most informative boolean function" conjecture of Courtade and Kumar for high noise $\epsilon \ge 1/2 - \delta$, for some absolute constant $\delta > 0$. #R##N#Namely, if $X$ is uniformly distributed in $\{0,1\}^n$ and $Y$ is obtained by flipping each coordinate of $X$ independently with probability $\epsilon$, then, provided $\epsilon \ge 1/2 - \delta$, for any boolean function $f$ holds $I(f(X);Y) \le 1 - H(\epsilon)$. This conjecture was previously known to hold only for balanced functions.

Connected through hyperedge HE-1 (induced by source paper "principal inertia components and applications"):
  with members:
    - "brascamp lieb inequality and its reverse an information theoretic view"
    - "bounds between contraction coefficients"
    - "on the duality of additivity and tensorization"
    - "managing your private and public data bringing down inference attacks against your privacy"
    - "remarks on the most informative function conjecture at fixed mean"
    - "euclidean information theory of networks"
    - "notes on information theoretic privacy"
    - "an improved upper bound for the most informative boolean function conjecture"

Connected through hyperedge HE-2 (induced by source paper "on the optimal boolean function for prediction under quadratic loss"):
  with members:
    - "on the entropy of a noisy function"
    - "an improved upper bound for the most informative boolean function conjecture"
    - "analysis of boolean functions"
    - "an exploration of the role of principal inertia components in information theory"

Connected through hyperedge HE-3 (induced by source paper "the maximum mutual information between the output of a binary symmetric channel and a boolean function of its input"):
  with members:
    - "on the entropy of a noisy function"
    - "an improved upper bound for the most informative boolean function conjecture"
    - "an exploration of the role of principal inertia components in information theory"

Connected through hyperedge HE-4 (induced by source paper "an improved upper bound for the most informative boolean function conjecture"):
  with members:
    - "on the entropy of a noisy function"
    - "analysis of boolean functions"

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)