human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "decidability of non interactive simulation of joint distributions"):
  Abstract: We present decidability results for a sub-class of "non-interactive" simulation problems, a well-studied class of problems in information theory. A non-interactive simulation problem is specified by two distributions $P(x,y)$ and $Q(u,v)$: The goal is to determine if two players, Alice and Bob, that observe sequences $X^n$ and $Y^n$ respectively where $\{(X_i, Y_i)\}_{i=1}^n$ are drawn i.i.d. from $P(x,y)$ can generate pairs $U$ and $V$ respectively (without communicating with each other) with a joint distribution that is arbitrarily close in total variation to $Q(u,v)$. Even when $P$ and $Q$ are extremely simple: e.g., $P$ is uniform on the triples $\{(0,0), (0,1), (1,0)\}$ and $Q$ is a "doubly symmetric binary source", i.e., $U$ and $V$ are uniform $\pm 1$ variables with correlation say $0.49$, it is open if $P$ can simulate $Q$. #R##N#In this work, we show that whenever $P$ is a distribution on a finite domain and $Q$ is a $2 \times 2$ distribution, then the non-interactive simulation problem is decidable: specifically, given $\delta > 0$ the algorithm runs in time bounded by some function of $P$ and $\delta$ and either gives a non-interactive simulation protocol that is $\delta$-close to $Q$ or asserts that no protocol gets $O(\delta)$-close to $Q$. The main challenge to such a result is determining explicit (computable) convergence bounds on the number $n$ of samples that need to be drawn from $P(x,y)$ to get $\delta$-close to $Q$. We invoke contemporary results from the analysis of Boolean functions such as the invariance principle and a regularity lemma to obtain such explicit bounds.

Includes members:
  Member "on the role of shared randomness in simultaneous communication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "round complexity of common randomness generation the amortized setting")
  Member "information complexity is computable":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "information complexity of the and function in the two party and multiparty settings")
  Member "on the duality of additivity and tensorization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "communication for generating correlation a unifying survey")
  Member "on non interactive simulation of joint distributions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "communication for generating correlation a unifying survey")
  Member "communication complexity of permutation invariant functions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "round complexity of common randomness generation the amortized setting")
  Member "communication with imperfectly shared randomness":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "round complexity of common randomness generation the amortized setting")
  Member "information equals amortized communication":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "communication for generating correlation a unifying survey")
  Member "reductions between expansion problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "bisect and conquer hierarchical clustering via max uncut bisection")

Question: Please tell me which class the source paper 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)