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 polynomial kernels for sparse integer linear programs"
  Abstract: Integer linear programs (ILPs) are a widely applied framework for dealing with combinatorial problems that arise in practice. It is known, e.g., by the success of CPLEX, that preprocessing and simplification can greatly speed up the process of optimizing an ILP. The present work seeks to further the theoretical understanding of preprocessing for ILPs by initiating a rigorous study within the framework of parameterized complexity and kernelization. #R##N#A famous result of Lenstra (Mathematics of Operations Research, 1983) shows that feasibility of any ILP with n variables and m constraints can be decided in time O(c^{n^3} m^c'). Thus, by a folklore argument, any such ILP admits a kernelization to an equivalent instance of size O(c^{n^3}). It is known, that unless NP \subseteq coNP/poly and the polynomial hierarchy collapses, no kernelization with size bound polynomial in n is possible. However, this lower bound only applies for the case when constraints may include an arbitrary number of variables since it follows from lower bounds for Satisfiability and Hitting Set, whose bounded arity variants admit polynomial kernelizations. #R##N#We consider the feasibility problem for ILPs Ax<= b where A is an r-row-sparse matrix parameterized by the number of variables. We show that the kernelizability of this problem depends strongly on the range of the variables. If the range is unbounded then this problem does not admit a polynomial kernelization unless NP \subseteq coNP/poly. If, on the other hand, the range of each variable is polynomially bounded in n then we do get a polynomial kernelization. Additionally, this holds also for the more general case when the maximum range d is an additional parameter, i.e., the size obtained is polynomial in n+d.

Connected through hyperedge HE-1 (induced by source paper "scheduling kernels via configuration lp"):
  with members:
    - "parameterized algorithms and data reduction for the short secluded s t path problem"
    - "multitype integer monoid optimization and applications"
    - "a parameterized strongly polynomial algorithm for block structured integer programs"
    - "scheduling meets n fold integer programming"
    - "combinatorial n fold integer programming and applications"
    - "interval scheduling and colorful independent sets"
    - "on polynomial kernels for integer linear programs covering packing and feasibility"

Connected through hyperedge HE-2 (induced by source paper "covering a tree with rooted subtrees"):
  with members:
    - "scheduling meets n fold integer programming"
    - "closing the gap for makespan scheduling via sparsification techniques"
    - "a structural approach to kernels for ilps treewidth and total unimodularity"
    - "on the optimality of approximation schemes for the classical scheduling problem"

Connected through hyperedge HE-3 (induced by source paper "combinatorial n fold integer programming and applications"):
  with members:
    - "a parameterized strongly polynomial algorithm for block structured integer programs"
    - "on integer programming and convolution"
    - "scheduling meets n fold integer programming"
    - "the complexity landscape of decompositional parameters for ilp"
    - "proximity results and faster algorithms for integer programming using the steinitz lemma"
    - "simplified algorithmic metatheorems beyond mso treewidth and neighborhood diversity"
    - "voting and bribing in single exponential time"
    - "about the structure of the integer cone and its application to bin packing"

Connected through hyperedge HE-4 (induced by source paper "a structural approach to kernels for ilps treewidth and total unimodularity"):
  with members:
    - "on polynomial kernels for integer linear programs covering packing and feasibility"
    - "kernelization lower bounds by cross composition"
    - "linear kernels and single exponential algorithms via protrusion decompositions"

Connected through hyperedge HE-5 (induced by source paper "on polynomial kernels for integer linear programs covering packing and feasibility"):
  with members:
    - "reducing a target interval to a few exact queries"
    - "hierarchies of inefficient kernelizability"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"
    - "cross composition a new technique for kernelization lower bounds"

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.CC(Computational Complexity)