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 "the communication complexity of set intersection and multiple equality testing"):
  Abstract: In this paper we explore fundamental problems in randomized communication complexity such as computing Set Intersection on sets of size $k$ and Equality Testing between vectors of length $k$. Brody et al. and Saglam and Tardos showed that for these types of problems, one can achieve optimal communication volume of $O(k)$ bits, with a randomized protocol that takes $O(\log^* k)$ rounds. #R##N#Aside from rounds and communication volume, there is a \emph{third} parameter of interest, namely the \emph{error probability} $p_{\mathrm{err}}$. It is straightforward to show that protocols for Set Intersection or Equality Testing need to send $\Omega(k + \log p_{\mathrm{err}}^{-1})$ bits. Is it possible to simultaneously achieve optimality in all three parameters, namely $O(k + \log p_{\mathrm{err}}^{-1})$ communication and $O(\log^* k)$ rounds? #R##N#In this paper we prove that there is no universally optimal algorithm, and complement the existing round-communication tradeoffs with a new tradeoff between rounds, communication, and probability of error. In particular: #R##N#1. Any protocol for solving Multiple Equality Testing in $r$ rounds with failure probability $2^{-E}$ has communication volume $\Omega(Ek^{1/r})$. #R##N#2. There exists a protocol for solving Multiple Equality Testing in $r + \log^*(k/E)$ rounds with $O(k + rEk^{1/r})$ communication, thereby essentially matching our lower bound and that of Saglam and Tardos. #R##N#Our original motivation for considering $p_{\mathrm{err}}$ as an independent parameter came from the problem of enumerating triangles in distributed ($\textsf{CONGEST}$) networks having maximum degree $\Delta$. We prove that this problem can be solved in $O(\Delta/\log n + \log\log \Delta)$ time with high probability $1-1/\operatorname{poly}(n)$.

Includes members:
  Member "improved distributed expander decomposition and nearly optimal triangle enumeration":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond")
  Member "distributed triangle detection via expander decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "detecting cliques in congest networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "fooling views a new lower bound technique for distributed computations under congestion":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "triangle finding and listing in congest networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "deterministic subgraph detection in broadcast congest":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "communication complexity for algorithm designers":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "complexity theory game theory and economics the barbados lectures")
  Member "on the communication complexity of sparse set disjointness and exists equal problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "near log convexity of measured heat in discrete time and consequences")

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)