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 "linear programming approximations for index coding"):
  Abstract: Index coding, a source coding problem over broadcast channels, has been a subject of both theoretical and practical interest since its introduction (by Birk and Kol, 1998). In short, the problem can be defined as follows: there is an input $\textbf{x} \triangleq (\textbf{x}_1, \dots, \textbf{x}_n)$, a set of $n$ clients who each desire a single symbol $\textbf{x}_i$ of the input, and a broadcaster whose goal is to send as few messages as possible to all clients so that each one can recover its desired symbol. Additionally, each client has some predetermined "side information," corresponding to certain symbols of the input $\textbf{x}$, which we represent as the "side information graph" $\mathcal{G}$. The graph $\mathcal{G}$ has a vertex $v_i$ for each client and a directed edge $(v_i, v_j)$ indicating that client $i$ knows the $j$th symbol of the input. Given a fixed side information graph $\mathcal{G}$, we are interested in determining or approximating the "broadcast rate" of index coding on the graph, i.e. the fewest number of messages the broadcaster can transmit so that every client gets their desired information. #R##N#Using index coding schemes based on linear programs (LPs), we take a two-pronged approach to approximating the broadcast rate. First, extending earlier work on planar graphs, we focus on approximating the broadcast rate for special graph families such as graphs with small chromatic number and disk graphs. In certain cases, we are able to show that simple LP-based schemes give constant-factor approximations of the broadcast rate, which seem extremely difficult to obtain in the general case. Second, we provide several LP-based schemes for the general case which are not constant-factor approximations, but which strictly improve on the prior best-known schemes.

Includes members:
  Member "the optimality of partial clique covering for index coding":
    also connected through other hyperedges:
      (none)
  Member "approximate capacity of index coding for some classes of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the optimality of partial clique covering for index coding")
  Member "storage capacity of repairable networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on an equivalence between single server pir with side information and locally recoverable codes")
  Member "generalized interlinked cycle cover for index coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rate frac 1 3 index coding forbidden and feasible configurations")
  Member "a new index coding scheme exploiting interlinked cycles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the single uniprior index coding problem the single sender case and the multi sender extension")
  Member "graph theory versus minimum rank for index coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "embedded index coding")
  Member "local graph coloring and index coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "embedded index coding")
  Member "lexicographic products and the power of non linear network coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an index coding approach to caching with uncoded cache placement")

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)