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: "improved inapproximability results for maximum k colorable subgraph"
  Abstract: We study the maximization version of the fundamental graph coloring problem. Here the goal is to color the vertices of a k -colorable graph with k colors so that a maximum fraction of edges are properly colored (i.e. their endpoints receive different colors). A random k -coloring properly colors an expected fraction $1-\frac{1}{k}$ of edges. We prove that given a graph promised to be k -colorable, it is NP-hard to find a k -coloring that properly colors more than a fraction           of edges. Previously, only a hardness factor of $1- O\bigl(\frac{1}{k^2}\bigr)$ was known. Our result pins down the correct asymptotic dependence of the approximation factor on k . Along the way, we prove that approximating the Maximum 3-colorable subgraph problem within a factor greater than $\frac{32}{33}$ is NP-hard.#R##N##R##N#Using semidefinite programming, it is known that one can do better than a random coloring and properly color a fraction $1-\frac{1}{k} +\frac{2 \ln k}{k^2}$ of edges in polynomial time. We show that, assuming the 2-to-1 conjecture, it is hard to properly color (using k colors) more than a fraction $1-\frac{1}{k} + O\left(\frac{\ln k}{k^2}\right)$ of edges of a k -colorable graph.

Connected through hyperedge HE-1 (induced by source paper "the maximum binary tree problem"):
  with members:
    - "narrow sieves for parameterized paths and packings"

Connected through hyperedge HE-2 (induced by source paper "new np hardness results for 3 coloring and 2 to 1 label cover"):
  with members:
    - "a new point of np hardness for 2 to 1 label cover"
    - "rounding semidefinite programming hierarchies via global correlation"
    - "lasserre hierarchy higher eigenvalues and approximation schemes for quadratic integer programming with psd objectives"
    - "approximation resistant predicates from pairwise independence"
    - "conditional hardness for approximate coloring"

Connected through hyperedge HE-3 (induced by source paper "a new point of np hardness for 2 to 1 label cover"):
  with members:
    - "rounding semidefinite programming hierarchies via global correlation"
    - "lasserre hierarchy higher eigenvalues and approximation schemes for quadratic integer programming with psd objectives"
    - "approximation resistant predicates from pairwise independence"
    - "conditional hardness for approximate coloring"

Connected through hyperedge HE-4 (induced by source paper "on unique games with negative weights"):
  with members:
    - "conditional hardness for approximate coloring"

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)