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: "alphabet sizes of auxiliary random variables in canonical inner bounds"
  Abstract: Recently, we proposed canonical inner bounds for a broad class of multiterminal source coding problems, subsuming an array of known results. Computation of those bounds assumes importance in view of open tightness questions, as well as their role as benchmarks, and in other contexts. In this backdrop, as computational algorithms depend exponentially on alphabet sizes of auxiliary random variables, estimating their sizes remains an important task. In existing literature, each auxiliary alphabet size is bounded within a positive integer constant of the corresponding source alphabet size. In a significant improvement, we give a tight bound, by showing that this constant integer can in fact be set to zero.

Connected through hyperedge HE-1 (induced by source paper "the minimal compression rate for similarity identification"):
  with members:
    - "compression for quadratic similarity queries"
    - "fixed length lossy compression in the finite blocklength regime"
    - "the dispersion of lossy source coding"
    - "an optimal bloom filter replacement based on matrix solving"

Connected through hyperedge HE-2 (induced by source paper "distributed and cascade lossy source coding with a side information vending machine"):
  with members:
    - "on real time coding with limited lookahead"
    - "multi terminal source coding with action dependent side information"
    - "robust coding for lossy computing with receiver side observation costs"
    - "source coding with a side information vending machine"
    - "on the role of mmse estimation in approaching the information theoretic limits of linear gaussian channels shannon meets wiener"

Connected through hyperedge HE-3 (induced by source paper "multiterminal source coding under logarithmic loss"):
  with members:
    - "multiterminal source coding with an entropy based distortion measure"
    - "rate region of the quadratic gaussian two encoder source coding problem"

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)