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: "on extracting common random bits from correlated sources on large alphabets"
  Abstract: Suppose Alice and Bob receive strings $X=(X_1,...,X_n)$ and $Y=(Y_1,...,Y_n)$ each uniformly random in $[s]^n$ but so that $X$ and $Y$ are correlated . For each symbol $i$, we have that $Y_i = X_i$ with probability $1-\eps$ and otherwise $Y_i$ is chosen independently and uniformly from $[s]$. #R##N#Alice and Bob wish to use their respective strings to extract a uniformly chosen common sequence from $[s]^k$ but without communicating. How well can they do? The trivial strategy of outputting the first $k$ symbols yields an agreement probability of $(1 - \eps + \eps/s)^k$. In a recent work by Bogdanov and Mossel it was shown that in the binary case where $s=2$ and $k = k(\eps)$ is large enough then it is possible to extract $k$ bits with a better agreement probability rate. In particular, it is possible to achieve agreement probability $(k\eps)^{-1/2} \cdot 2^{-k\eps/(2(1 - \eps/2))}$ using a random construction based on Hamming balls, and this is optimal up to lower order terms. #R##N#In the current paper we consider the same problem over larger alphabet sizes $s$ and we show that the agreement probability rate changes dramatically as the alphabet grows. In particular we show no strategy can achieve agreement probability better than $(1-\eps)^k (1+\delta(s))^k$ where $\delta(s) \to 0$ as $s \to \infty$. We also show that Hamming ball based constructions have {\em much lower} agreement probability rate than the trivial algorithm as $s \to \infty$. Our proofs and results are intimately related to subtle properties of hypercontractive inequalities.

Connected through hyperedge HE-1 (induced by source paper "communication for generating correlation a unifying survey"):
  with members:
    - "secret key capacity for multipleaccess channel with public feedback"
    - "exact exponent for soft covering"
    - "exact channel synthesis"
    - "strong converse using change of measure arguments"
    - "coding for positive rate in the source model key agreement problem"
    - "wiretap channels nonasymptotic fundamental limits"
    - "channel resolvability theorems for general sources and channels"
    - "strong functional representation lemma and applications to coding theorems"

Connected through hyperedge HE-2 (induced by source paper "communication for generating correlation a survey"):
  with members:
    - "secret key capacity for multipleaccess channel with public feedback"
    - "exact soft covering exponent"
    - "on exact and infty r enyi common informations"
    - "exact channel synthesis"
    - "strong converse using change of measure arguments"
    - "coding for positive rate in the source model key agreement problem"
    - "wiretap channels nonasymptotic fundamental limits"
    - "channel resolvability theorems for general sources and channels"

Connected through hyperedge HE-3 (induced by source paper "round complexity of common randomness generation the amortized setting"):
  with members:
    - "communication rounds tradeoffs for common randomness and secret key generation"
    - "resource efficient common randomness and secret key schemes"
    - "the power of shared randomness in uncertain communication"
    - "secret key generation with limited interaction"
    - "on the role of shared randomness in simultaneous communication"
    - "secret key generation with one communicator and a one shot converse via hypercontractivity"
    - "communication complexity of permutation invariant functions"
    - "communication with imperfectly shared randomness"

Connected through hyperedge HE-4 (induced by source paper "communication rounds tradeoffs for common randomness and secret key generation"):
  with members:
    - "dimension reduction for polynomials over gaussian space and applications"
    - "resource efficient common randomness and secret key schemes"
    - "decidability of non interactive simulation of joint distributions"
    - "on the role of shared randomness in simultaneous communication"
    - "on non interactive simulation of joint distributions"
    - "communication complexity of permutation invariant functions"
    - "on maximal correlation hypercontractivity and the data processing inequality studied by erkip and cover"
    - "common information and secret key capacity"

Connected through hyperedge HE-5 (induced by source paper "resource efficient common randomness and secret key schemes"):
  with members:
    - "common randomness and key generation with limited interaction"
    - "on the role of shared randomness in simultaneous communication"
    - "secret key generation with one communicator and a one shot converse via hypercontractivity"
    - "on maximal correlation hypercontractivity and the data processing inequality studied by erkip and cover"

Connected through hyperedge HE-6 (induced by source paper "communication complexity of permutation invariant functions"):
  with members:
    - "on the role of shared randomness in simultaneous communication"
    - "information complexity is computable"
    - "communication with imperfectly shared randomness"
    - "on the communication complexity of sparse set disjointness and exists equal problems"
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "an optimal lower bound on the communication complexity of gap hamming distance"
    - "on extracting common random bits from correlated sources"
    - "the partition bound for classical communication complexity and query complexity"

Connected through hyperedge HE-7 (induced by source paper "random walks and evolving sets faster convergences and limitations"):
  with members:
    - "improved cheeger s inequality and analysis of local graph partitioning using vertex expansion and expansion profile"
    - "analysis of boolean functions"
    - "local graph clustering beyond cheeger s inequality"
    - "improved cheeger s inequality analysis of spectral partitioning algorithms through higher order spectral gap"
    - "a local clustering algorithm for massive graphs and its application to nearly linear time graph partitioning"
    - "finding sparse cuts locally using evolving sets"
    - "max cut and the smallest eigenvalue"

Connected through hyperedge HE-8 (induced by source paper "communication with imperfectly shared randomness"):
  with members:
    - "on the role of shared randomness in simultaneous communication"
    - "on the duality of additivity and tensorization"
    - "minimum hgr correlation principle from marginals to joint distribution"
    - "analysis of boolean functions"
    - "deterministic compression with uncertain priors"
    - "on extracting common random bits from correlated sources"

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)