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 "optimized sensor collaboration for estimation of temporally correlated parameters"):
  Abstract: In this paper, we aim to design the optimal sensor collaboration strategy for the estimation of time-varying parameters, where collaboration refers to the act of sharing measurements with neighboring sensors prior to transmission to a fusion center. We begin by addressing the sensor collaboration problem for the estimation of uncorrelated parameters. We show that the resulting collaboration problem can be transformed into a special nonconvex optimization problem, where a difference of convex functions carries all the nonconvexity. This specific problem structure enables the use of a convex–concave procedure to obtain a near-optimal solution. When the parameters of interest are temporally correlated, a penalized version of the convex–concave procedure becomes well suited for designing the optimal collaboration scheme. In order to improve computational efficiency, we further propose a fast algorithm that scales gracefully with problem size via the alternating direction method of multipliers. Numerical results are provided to demonstrate the effectiveness of our approach and the impact of parameter correlation and temporal dynamics of sensor networks on estimation performance.

Includes members:
  Member "network topology adaptation and interference coordination for energy saving in heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy management in heterogeneous networks with cell activation user association and interference coordination")
  Member "large scale convex optimization for dense wireless cooperative networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "large scale beamforming for massive mimo via randomized sketching")
  Member "optimal power allocation for distributed blue estimation with linear spatial collaboration":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy balancing for robotic aided clustered wireless sensor networks using mobility diversity algorithms")
  Member "distributed estimation and detection with bounded transmissions over gaussian multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed nonparametric sequential spectrum sensing under electromagnetic interference")
  Member "controlled collaboration for linear coherent estimation in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the effect of correlated observations on the performance of distributed estimation")
  Member "optimal identical binary quantizer design for distributed estimation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "detection under one bit messaging over adaptive networks")
  Member "on linear coherent estimation with spatial collaboration":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "controlled collaboration for linear coherent estimation in wireless sensor networks")
  Member "distributed detection over fading macs with multiple antennas at the fusion center":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "estimation in phase shift and forward wireless sensor networks")

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.IT(Information Theory)