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: "lossless source coding in the point to point multiple access and random access scenarios"
  Abstract: This paper treats point-to-point, multiple access and random access lossless source coding in the finite-blocklength regime. A random coding technique is developed, and its power in analyzing the third-order-optimal coding performance is demonstrated in all three scenarios. Results include a third-order-optimal characterization of the Slepian-Wolf rate region and a proof showing that for dependent sources, the independent encoders used by Slepian-Wolf codes can achieve the same third-order-optimal performance as a single joint encoder. The concept of random access source coding, which generalizes the multiple access scenario to allow for a number of participating encoders that is unknown a priori to both the encoders and the decoder, is introduced. Contributions include a new definition of the probabilistic model for a random access-discrete multiple source (RA-DMS), a general random access source coding scheme that employs a rateless code with sporadic feedback, and an analysis for the proposed scheme demonstrating via a random coding argument that there exists a deterministic code of the proposed structure that simultaneously achieves the third-order-optimal performance of Slepian-Wolf codes for all possible numbers of encoders. While the analysis for random access codes focuses on a class of permutation-invariant RA-DMSs, it also extends to more general sources.

Connected through hyperedge HE-1 (induced by source paper "gaussian multiple and random access in the finite blocklength regime"):
  with members:
    - "fundamental limits of many user mac with finite payloads and fading"
    - "random access channel coding in the finite blocklength regime"
    - "capacity of gaussian many access channels"
    - "a proof of the strong converse theorem for gaussian multiple access channels"
    - "the third order term in the normal approximation for the awgn channel"
    - "many access channels the gaussian case with random user activities"
    - "on the dispersions of three network information theory problems"
    - "second order rate region of constant composition codes for the multiple access channel"

Connected through hyperedge HE-2 (induced by source paper "fundamental limits of lossless data compression with side information"):
  with members:
    - "improved finite blocklength converses for slepian wolf coding via linear programming"
    - "on the dispersions of three network information theory problems"
    - "reference based genome compression"
    - "second order slepian wolf coding theorems for non mixed and mixed sources"

Connected through hyperedge HE-3 (induced by source paper "random access channel coding in the finite blocklength regime"):
  with members:
    - "capacity of gaussian many access channels"
    - "a proof of the strong converse theorem for gaussian multiple access channels"
    - "many access channels the gaussian case with random user activities"
    - "on the dispersions of three network information theory problems"
    - "aloha random access that operates as a rateless code"
    - "second order rate region of constant composition codes for the multiple access channel"
    - "random access an information theoretic perspective"

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)