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: "geographic gossip efficient aggregation for sensor networks"
  Abstract: Gossip algorithms for aggregation have recently received significant attention for sensor network applications because of their simplicity and robustness in noisy and uncertain environments. However, gossip algorithms can waste significant energy by essentially passing around redundant information multiple times. For realistic sensor network model topologies like grids and random geometric graphs, the inefficiency of gossip schemes is caused by slow mixing times of random walks on those graphs. We propose and analyze an alternative gossiping scheme that exploits geographic information. By utilizing a simple resampling method, we can demonstrate substantial gains over previously proposed gossip protocols. In particular, for random geometric graphs, our algorithm computes the true average to accuracy $1/n^a$ using $O(n^{1.5}\sqrt{\log n})$ radio transmissions, which reduces the energy consumption by a $\sqrt{\frac{n}{\log n}}$ factor over standard gossip algorithms.

Connected through hyperedge HE-1 (induced by source paper "a survey of distributed data aggregation algorithms"):
  with members:
    - "spectra robust estimation of distribution functions in networks"
    - "fault tolerant aggregation flow updating meets mass distribution"
    - "dependability in aggregation by averaging"
    - "a survey of green networking research"
    - "geographic gossip efficient averaging for sensor networks"
    - "dynamic approaches to in network aggregation"
    - "fast distributed algorithms for computing separable functions"
    - "medians and beyond new aggregation techniques for sensor networks"

Connected through hyperedge HE-2 (induced by source paper "network coding for computing cut set bounds"):
  with members:
    - "communicating the sum of sources over a network"
    - "cascade multiterminal source coding"
    - "feasible alphabets for communicating the sum of sources over a network"
    - "some bounds on the capacity of communicating the sum of sources"
    - "information theoretic bounds for multiround function computation in collocated networks"
    - "fast distributed algorithms for computing separable functions"

Connected through hyperedge HE-3 (induced by source paper "convergence speed of the consensus algorithm with interference and sparse long range connectivity"):
  with members:
    - "location aided fast distributed consensus in wireless networks"
    - "sensor networks with random links topology design for distributed consensus"
    - "distance distributions in finite uniformly random networks theory and applications"
    - "network based consensus averaging with general noisy channels"

Connected through hyperedge HE-4 (induced by source paper "a modeling framework for gossip based information spread"):
  with members:
    - "an analytical model of information dissemination for a gossip based protocol"

Connected through hyperedge HE-5 (induced by source paper "gossip algorithms for distributed signal processing"):
  with members:
    - "location aided fast distributed consensus in wireless networks"
    - "weight optimization for consensus algorithms with correlated switching topology"
    - "optimization and analysis of distributed averaging with short node memory"
    - "distributed lossy averaging"
    - "polynomial filtering for fast convergence in distributed consensus"
    - "distributed sensor localization in random environments using minimal number of anchor nodes"
    - "the impact of mobility on gossip algorithms"
    - "distributed parameter estimation in sensor networks nonlinear observation models and imperfect communication"

Connected through hyperedge HE-6 (induced by source paper "location aided fast distributed consensus in wireless networks"):
  with members:
    - "geographic gossip efficient averaging for sensor networks"
    - "order optimal consensus through randomized path averaging"

Connected through hyperedge HE-7 (induced by source paper "greedy gossip with eavesdropping"):
  with members:
    - "distributed and recursive parameter estimation in parametrized linear state space models"

Connected through hyperedge HE-8 (induced by source paper "optimal gossip based aggregate computation"):
  with members:
    - "medians and beyond new aggregation techniques for sensor networks"

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.IT(Information Theory)