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: "toward resource optimal consensus over the wireless medium"
  Abstract: We carry out a comprehensive study of the resource cost of averaging consensus in wireless networks. Most previous approaches suppose a graphical network, which abstracts away crucial features of the wireless medium, and measure resource consumption only in terms of the total number of transmissions required to achieve consensus. Under a path-loss model, we study the resource requirements of consensus with respect to three wireless-appropriate metrics: total transmit energy, elapsed time, and time-bandwidth product. First, we characterize the performance of several popular gossip algorithms, showing that they may be order-optimal with respect to transmit energy but are strictly suboptimal with respect to elapsed time and time-bandwidth product. Further, we propose a new consensus scheme, termed hierarchical averaging, and show that it is nearly order-optimal with respect to all three metrics. Finally, we examine the effects of quantization, showing that hierarchical averaging provides a nearly order-optimal tradeoff between resource consumption and quantization error.

Connected through hyperedge HE-1 (induced by source paper "multi scale spectrum sensing in dense multi cell cognitive networks"):
  with members:
    - "a parallel algorithm for generating a random graph with a prescribed degree sequence"
    - "multi scale spectrum sensing in small cell mm wave cognitive wireless networks"
    - "understanding noise and interference regimes in 5g millimeter wave cellular networks"
    - "investigation of prediction accuracy sensitivity and parameter stability of large scale propagation path loss models for 5g wireless communications"
    - "gains of restricted secondary licensing in millimeter wave cellular systems"
    - "cross layer design of distributed sensing estimation with quality feedback part i optimal schemes"
    - "cross layer estimation and control for cognitive radio exploiting sparse network dynamics"
    - "exploiting device to device communications in joint scheduling of access and backhaul for mmwave small cells"

Connected through hyperedge HE-2 (induced by source paper "multi scale spectrum sensing in 5g cognitive networks"):
  with members:
    - "multi scale spectrum sensing in small cell mm wave cognitive wireless networks"
    - "understanding noise and interference regimes in 5g millimeter wave cellular networks"
    - "gains of restricted secondary licensing in millimeter wave cellular systems"
    - "cross layer design of distributed sensing estimation with quality feedback part i optimal schemes"
    - "cross layer estimation and control for cognitive radio exploiting sparse network dynamics"
    - "exploiting device to device communications in joint scheduling of access and backhaul for mmwave small cells"
    - "tractable model for rate in self backhauled millimeter wave cellular networks"
    - "coverage and rate analysis for millimeter wave cellular networks"

Connected through hyperedge HE-3 (induced by source paper "source coding optimization for distributed average consensus"):
  with members:
    - "performance limits for noisy multimeasurement vector problems"
    - "an overview of multi processor approximate message passing"
    - "statistical physics and information theory perspectives on linear inverse problems"
    - "optimal trade offs in multi processor approximate message passing"
    - "multi processor approximate message passing using lossy compression"
    - "distributed parameter estimation with quantized communication via running average"
    - "on constrained randomized quantization"
    - "non asymptotic analysis of an optimal algorithm for network constrained averaging with noisy links"

Connected through hyperedge HE-4 (induced by source paper "generalized geometric programming for rate allocation in consensus"):
  with members:
    - "an overview of multi processor approximate message passing"
    - "optimal trade offs in multi processor approximate message passing"
    - "cloud k svd a collaborative dictionary learning algorithm for big distributed data"
    - "performance trade offs in multi processor approximate message passing"
    - "non asymptotic analysis of an optimal algorithm for network constrained averaging with noisy links"
    - "gossip algorithms for distributed signal processing"
    - "distributed lossy averaging"
    - "network based consensus averaging with general noisy channels"

Connected through hyperedge HE-5 (induced by source paper "multi scale spectrum sensing in small cell mm wave cognitive wireless networks"):
  with members:
    - "cross layer estimation and control for cognitive radio exploiting sparse network dynamics"
    - "tractable model for rate in self backhauled millimeter wave cellular networks"
    - "coverage and rate analysis for millimeter wave cellular networks"
    - "order optimal consensus through randomized path averaging"

Connected through hyperedge HE-6 (induced by source paper "distributed inference for relay assisted sensor networks with intermittent measurements over fading channels"):
  with members:
    - "convergence rate analysis of distributed gossip linear parameter estimation fundamental limits and tradeoffs"
    - "the role of persistent graphs in the agreement seeking of social networks"
    - "distributed parameter estimation in sensor networks nonlinear observation models and imperfect communication"
    - "sensor networks with random links topology design for distributed consensus"
    - "distributed decision through self synchronizing sensor networks in the presence of propagation delays and nonreciprocal channels"

Connected through hyperedge HE-7 (induced by source paper "on decentralized estimation with active queries"):
  with members:
    - "collaborative 20 questions for target localization"
    - "convergence rate analysis of distributed gossip linear parameter estimation fundamental limits and tradeoffs"
    - "active testing for face detection and localization"
    - "gossip algorithms for distributed signal processing"
    - "order optimal consensus through randomized path averaging"

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)