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: "exploiting spontaneous transmissions for broadcasting and leader election in radio networks"
  Abstract: We study two fundamental communication primitives: broadcasting and leader election in the classical model of multi-hop radio networks with unknown topology and without collision detection mechanisms. #R##N#It has been known for almost 20 years that in undirected networks with n nodes and diameter D, randomized broadcasting requires Omega(D log n/D + log^2 n) rounds in expectation, assuming that uninformed nodes are not allowed to communicate (until they are informed). Only very recently, Haeupler and Wajc (PODC'2016) showed that this bound can be slightly improved for the model with spontaneous transmissions, providing an O(D log n loglog n / log D + log^O(1) n)-time broadcasting algorithm. In this paper, we give a new and faster algorithm that completes broadcasting in O(D log n/log D + log^O(1) n) time, with high probability. This yields the first optimal O(D)-time broadcasting algorithm whenever D is polynomial in n. #R##N#Furthermore, our approach can be applied to design a new leader election algorithm that matches the performance of our broadcasting algorithm. Previously, all fast randomized leader election algorithms have been using broadcasting as their subroutine and their complexity have been asymptotically strictly bigger than the complexity of broadcasting. In particular, the fastest previously known randomized leader election algorithm of Ghaffari and Haeupler (SODA'2013) requires O(D log n/D min{loglog n, log n/D} + log^O(1) n)-time with high probability. Our new algorithm requires O(D log n / log D + log^O(1) n) time with high probability, and it achieves the optimal O(D) time whenever D is polynomial in n.

Connected through hyperedge HE-1 (induced by source paper "competitive broadcast against adaptive adversary in multi channel radio networks"):
  with members:
    - "fast and resource competitive broadcast in multi channel radio networks"
    - "the energy complexity of broadcast"
    - "exponential separations in the energy complexity of leader election"
    - "interactive communication with unknown noise rate"
    - "randomized broadcast in radio networks with collision detection"
    - "making evildoers pay resource competitive broadcast in sensor networks"
    - "a resource competitive jamming defense"

Connected through hyperedge HE-2 (induced by source paper "deterministic leader election in anonymous radio networks"):
  with members:
    - "deterministic leader election in o d log n time with messages of size o 1"
    - "time vs information tradeoffs for leader election in anonymous trees"

Connected through hyperedge HE-3 (induced by source paper "fast and resource competitive broadcast in multi channel radio networks"):
  with members:
    - "the energy complexity of broadcast"
    - "randomized broadcast in radio networks with collision detection"
    - "making evildoers pay resource competitive broadcast in sensor networks"
    - "a resource competitive jamming defense"

Connected through hyperedge HE-4 (induced by source paper "randomized communication without network knowledge"):
  with members:
    - "deterministic blind radio networks"
    - "deterministic communication in radio networks"
    - "communicating with beeps"
    - "randomized broadcast in radio networks with collision detection"

Connected through hyperedge HE-5 (induced by source paper "the energy complexity of broadcast"):
  with members:
    - "exponential separations in the energy complexity of leader election"
    - "randomized broadcast in radio networks with collision detection"
    - "radio network lower bounds made easy"
    - "parallel graph decompositions using random shifts"
    - "near optimal leader election in multi hop radio networks"

Connected through hyperedge HE-6 (induced by source paper "broadcast in radio networks time vs energy tradeoffs"):
  with members:
    - "the energy complexity of broadcast"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "exponential separations in the energy complexity of leader election"
    - "randomized broadcast in radio networks with collision detection"

Connected through hyperedge HE-7 (induced by source paper "finding the size of a radio network with short labels"):
  with members:
    - "short labeling schemes for topology recognition in wireless tree networks"
    - "topology recognition with advice"
    - "time vs information tradeoffs for leader election in anonymous trees"
    - "randomized broadcast in radio networks with collision detection"

Connected through hyperedge HE-8 (induced by source paper "exponential separations in the energy complexity of leader election"):
  with members:
    - "the energy complexity of broadcast"
    - "broadcasting in noisy radio networks"
    - "the computational power of beeps"
    - "optimal leader election in multi hop radio networks"
    - "radio network lower bounds made easy"
    - "near optimal leader election in multi hop radio networks"
    - "deploying wireless networks with beeps"

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.DC(Distributed, Parallel, and Cluster Computing)