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 "intersensor collaboration in distributed quantization networks"):
  Abstract: Several key results in distributed source coding offer the intuition that little improvement in compression can be gained from intersensor communication when the information is coded in long blocks. However, when sensors are restricted to code their observations in small blocks (e.g., one) or desire fidelity of a computation applied to source realizations, intelligent collaboration between sensors can greatly reduce distortion. For networks where sensors are allowed to "chat" using a side channel that is unobservable at the fusion center, we provide asymptotically-exact characterization of distortion performance and optimal quantizer design in the high-resolution (low-distortion) regime using a framework called distributed functional scalar quantization (DFSQ). The key result is that chatting can dramatically improve performance even when intersensor communication is at very low rate. We also solve the rate allocation problem when communication links have heterogeneous costs and provide a detailed example to demonstrate the theoretical and practical gains from chatting. This example for maximum computation gives insight on the gap between chatting and distributed networks, and how to optimize the intersensor communication.

Includes members:
  Member "on the dispersions of three network information theory problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "distributed functional scalar quantization simplified":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on distributed quantization for classification")
  Member "on cooperation in multi terminal computation and rate distortion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rate distortion for lossy in network function computation information dissipation and sequential reverse water filling")
  Member "fixed length lossy compression in the finite blocklength regime":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "finite sample analysis of image registration")
  Member "distributed scalar quantization for computing high resolution analysis and extensions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on distributed quantization for classification")
  Member "the dispersion of lossy source coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sparse regression codes")
  Member "perfect omniscience perfect secrecy and steiner tree packing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "secret key agreement for hypergraphical sources with limited total discussion")

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)