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: "on the statistical physics of directed polymers in a random medium and their relation to tree codes"
  Abstract: Using well-known results from statistical physics, concerning the almost-sure behavior of the free energy of directed polymers in a random medium, we prove that random tree codes achieve the distortion-rate function almost surely under a certain symmetry condition.

Connected through hyperedge HE-1 (induced by source paper "another look at expurgated bounds and their statistical mechanical interpretation"):
  with members:
    - "rate distortion function via minimum mean square error estimation"
    - "the generalized random energy model and its application to the statistical physics of ensembles of hierarchical codes"
    - "error exponents for broadcast channels with degraded message sets"
    - "error exponents of optimum decoding for the interference channel"
    - "error exponents of erasure list decoding revisited via moments of distance enumerators"
    - "relations between random coding exponents and the statistical physics of random codes"

Connected through hyperedge HE-2 (induced by source paper "zero delay and causal single user and multi user lossy source coding with decoder side information"):
  with members:
    - "data processing bounds for scalar lossy source codes with side information at the decoder"
    - "structure theorems for real time variable rate coding with and without side information"
    - "multiterminal source coding under logarithmic loss"
    - "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)