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 index coding and graph homomorphism"
  Abstract: In this work, we study the problem of index coding from graph homomorphism perspective. We show that the minimum broadcast rate of an index coding problem for different variations of the problem such as non-linear, scalar, and vector index code, can be upper bounded by the minimum broadcast rate of another index coding problem when there exists a homomorphism from the complement of the side information graph of the first problem to that of the second problem. As a result, we show that several upper bounds on scalar and vector index code problem are special cases of one of our main theorems. #R##N#For the linear scalar index coding problem, it has been shown in [1] that the binary linear index of a graph is equal to a graph theoretical parameter called minrank of the graph. For undirected graphs, in [2] it is shown that $\mathrm{minrank}(G) = k$ if and only if there exists a homomorphism from $\bar{G}$ to a predefined graph $\bar{G}_k$. Combining these two results, it follows that for undirected graphs, all the digraphs with linear index of at most k coincide with the graphs $G$ for which there exists a homomorphism from $\bar{G}$ to $\bar{G}_k$. In this paper, we give a direct proof to this result that works for digraphs as well. #R##N#We show how to use this classification result to generate lower bounds on scalar and vector index. In particular, we provide a lower bound for the scalar index of a digraph in terms of the chromatic number of its complement. #R##N#Using our framework, we show that by changing the field size, linear index of a digraph can be at most increased by a factor that is independent from the number of the nodes.

Connected through hyperedge HE-1 (induced by source paper "index coding rank invariant extensions"):
  with members:
    - "uniprior index coding"
    - "structural properties of index coding capacity"
    - "the single uniprior index coding problem the single sender case and the multi sender extension"
    - "structural properties of index coding capacity using fractional graph theory"
    - "optimal vector linear index codes for some symmetric side information problems"
    - "on a duality between recoverable distributed storage and index coding"
    - "topological interference management through index coding"
    - "optimal index codes with near extreme rates"

Connected through hyperedge HE-2 (induced by source paper "the single uniprior index coding problem the single sender case and the multi sender extension"):
  with members:
    - "structural properties of index coding capacity using fractional graph theory"
    - "a new index coding scheme exploiting interlinked cycles"
    - "bounding multiple unicasts through index coding and locally repairable codes"
    - "linear codes are optimal for index coding instances with five or fewer receivers"
    - "a new class of index coding instances where linear coding is optimal"
    - "on the capacity region for index coding"
    - "duality codes and the integrality gap bound for index coding"
    - "fundamental limits of distributed caching in d2d wireless networks"

Connected through hyperedge HE-3 (induced by source paper "linear index coding via graph homomorphism"):
  with members:
    - "on the capacity region for index coding"
    - "local graph coloring and index coding"
    - "an equivalence between network coding and index coding"
    - "index coding an interference alignment perspective"
    - "optimal index codes with near extreme rates"
    - "on linear index coding for random graphs"
    - "linear index coding via semidefinite programming"
    - "index coding via linear programming"

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)