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: "balancing communication for multi party interactive coding"
  Abstract: We consider interactive coding in a setting where $n$ parties wish to compute a joint function of their inputs via an interactive protocol over imperfect channels. We assume that adversarial errors can comprise a $\mathcal{O}(\frac{1}{n})$ fraction of the total communication, occurring anywhere on the communication network. Our goal is to maintain a constant multiplicative overhead in the total communication required, as compared to the error-free setting, and also to balance the workload over the different parties. We build upon the prior protocol of Jain, Kalai, and Lewko, but while that protocol relies on a single coordinator to shoulder a heavy burden throughout the protocol, we design a mechanism to pass the coordination duties from party to party, resulting in a more even distribution of communication over the course of the computation.

Connected through hyperedge HE-1 (induced by source paper "making asynchronous distributed computations robust to noise"):
  with members:
    - "coding for interactive communication correcting insertions and deletions"
    - "maximal noise in interactive communication over erasure channels and channels with feedback"
    - "interactive channel capacity revisited"
    - "the adversarial noise threshold for distributed protocols"
    - "breathe before speaking efficient information dissemination despite noisy limited and anonymous communication"
    - "optimal error rates for interactive coding i adaptivity and other settings"
    - "optimal error rates for interactive coding ii efficiency and list decoding"

Connected through hyperedge HE-2 (induced by source paper "the adversarial noise threshold for distributed protocols"):
  with members:
    - "sparse sums of positive semidefinite matrices"
    - "maximal noise in interactive communication over erasure channels and channels with feedback"
    - "interactive channel capacity revisited"
    - "optimal error rates for interactive coding i adaptivity and other settings"
    - "optimal error rates for interactive coding ii efficiency and list decoding"
    - "tree codes and a conjecture on exponential sums"
    - "faster approximation schemes for fractional multicommodity flow problems via dynamic graph algorithms"
    - "twice ramanujan sparsifiers"

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.DS(Data Structures and Algorithms)