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 "unequal message protection asymptotic and non asymptotic tradeoffs"):
  Abstract: We study a form of unequal error protection that we term "unequal message protection" (UMP). The message set of a UMP code is a union of $m$ disjoint message classes. Each class has its own error protection requirement, with some classes needing better error protection than others. We analyze the tradeoff between rates of message classes and the levels of error protection of these codes. We demonstrate that there is a clear performance loss compared to homogeneous (classical) codes with equivalent parameters. This is in sharp contrast to previous literature that considers UMP codes. To obtain our results we generalize finite block length achievability and converse bounds due to Polyanskiy-Poor-Verd\'{u}. We evaluate our bounds for the binary symmetric and binary erasure channels, and analyze the asymptotic characteristic of the bounds in the fixed error and moderate deviations regimes. In addition, we consider two questions related to the practical construction of UMP codes. First, we study a "header" construction that prefixes the message class into a header followed by data protection using a standard homogeneous code. We show that, in general, this construction is not optimal at finite block lengths. We further demonstrate that our main UMP achievability bound can be obtained using coset codes, which suggests a path to implementation of tractable UMP codes.

Includes members:
  Member "a tight upper bound for the third order asymptotics for most discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "finite sample analysis of image registration")
  Member "random access and source channel coding error exponents for multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "error exponents for asynchronous multiple access channels controlled asynchronism may outperform synchronism")
  Member "the third order term in the normal approximation for singular channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "asymptotic estimates in information theory with non vanishing error probabilities")
  Member "the log volume of optimal codes for memoryless channels asymptotically within a few nats":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "finite sample analysis of image registration")
  Member "the awgn red alert problem":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hypothesis testing under mutual information privacy constraints in the high privacy regime")
  Member "moderate deviations in channel coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal resolution of change point detection with empirically observed statistics and erasures")
  Member "lossy joint source channel coding in the finite blocklength regime":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "finite sample analysis of image registration")
  Member "the dispersion of joint source channel coding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a lower bound on the expected distortion of joint source channel coding")

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)