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 "ant inspired density estimation via random walks"):
  Abstract: Many ant species employ distributed population density estimation in applications ranging from quorum sensing [Pra05], to task allocation [Gor99], to appraisal of enemy colony strength [Ada90]. It has been shown that ants estimate density by tracking encounter rates -- the higher the population density, the more often the ants bump into each other [Pra05,GPT93]. #R##N#We study distributed density estimation from a theoretical perspective. We show that a group of anonymous agents randomly walking on a grid are able to estimate their density $d$ to within a multiplicative factor $1 \pm \epsilon$ with probability $1-\delta$ in just $\tilde O \left (\frac{\log(1/\delta)\log(1/d\epsilon)}{d\epsilon^2} \right )$ steps by measuring their encounter rates with other agents. Despite dependencies inherent in the fact that nearby agents may collide repeatedly (and, worse, cannot recognize when this happens), this bound nearly matches what is required to estimate $d$ by independently sampling grid locations. #R##N#From a biological perspective, our work helps shed light on how ants and other social insects can obtain relatively accurate density estimates via encounter rates. From a technical perspective, our analysis provides new tools for understanding complex dependencies in the collision probabilities of multiple random walks. We bound the strength of these dependencies using $local\ mixing\ properties$ of the underlying graph. Our results extend beyond the grid to more general graphs and we discuss applications to social network size estimation, density estimation by robot swarms, and random walked-based sampling of sensor networks.

Includes members:
  Member "limits for rumor spreading in stochastic populations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "noidy conmunixatipn on the convergence of the averaging population protocol")
  Member "on coalescence time in graphs when is coalescing as fast as meeting":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the dispersion time of random walks on finite graphs")
  Member "graph size estimation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "true nonlinear dynamics from incomplete networks")
  Member "a walk in facebook uniform sampling of users in online social networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fairness in online social network timelines measurements models and mechanism design")

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.DC(Distributed, Parallel, and Cluster Computing)