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 "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.

Includes members:
  Member "encoding tasks and renyi entropy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "asymptotic expansions of smooth r e nyi entropies and their applications")
  Member "further results on geometric properties of a family of relative entropies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "minimization problems based on relative alpha entropy i forward projection")
  Member "guessing revisited a large deviations approach":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "practical estimation of renyi entropy")
  Member "guessing under source uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "generalized bayesian cramer rao inequality via information geometry of relative alpha entropy")

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)