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: "minimization problems based on a parametric family of relative entropies ii reverse projection"
  Abstract: In part I of this two-part work, certain minimization problems based on a parametric family of relative entropies (denoted $\mathscr{I}_{\alpha}$) were studied. Such minimizers were called forward $\mathscr{I}_{\alpha}$-projections. Here, a complementary class of minimization problems leading to the so-called reverse $\mathscr{I}_{\alpha}$-projections are studied. Reverse $\mathscr{I}_{\alpha}$-projections, particularly on log-convex or power-law families, are of interest in robust estimation problems ($\alpha >1$) and in constrained compression settings ($\alpha <1$). Orthogonality of the power-law family with an associated linear family is first established and is then exploited to turn a reverse $\mathscr{I}_{\alpha}$-projection into a forward $\mathscr{I}_{\alpha}$-projection. The transformed problem is a simpler quasiconvex minimization subject to linear constraints.

Connected through hyperedge HE-1 (induced by source paper "on the r e nyi divergence and the joint range of relative entropies"):
  with members:
    - "tight bounds for symmetric divergence measures and a refined bound for lossless source coding"
    - "information theoretic applications of the logarithmic probability comparison bound"
    - "on pairs of f divergences and their joint range"
    - "a note on a characterization of renyi measures and its relation to composite hypothesis testing"
    - "guessing under source uncertainty"
    - "tightened upper bounds on the ml decoding error probability of binary linear block codes"

Connected through hyperedge HE-2 (induced by source paper "minimization problems based on relative alpha entropy i forward projection"):
  with members:
    - "minimization problems based on relative alpha entropy ii reverse projection"
    - "relative alpha entropy minimizers subject to linear statistical constraints"
    - "encoding tasks and renyi entropy"
    - "renyi divergence and kullback leibler divergence"
    - "further results on geometric properties of a family of relative entropies"
    - "guessing revisited a large deviations approach"
    - "guessing under source uncertainty"

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)