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: "parameterized inapproximability of exact cover and nearest codeword"
  Abstract: The $k$-ExactCover problem is a parameterized version of the ExactCover problem, in which we are given a universe $U$, a collection $S$ of subsets of $U$, and an integer $k$, and the task is to determine whether $U$ can be partitioned into $k$ sets in $S$. This is a natural extension of the well-studied SetCover problem; though in the parameterized regime we know it to be $W[1]$-complete in the exact case, its parameterized complexity with respect to approximability is not well understood. #R##N#We prove that, assuming ETH, for some $\gamma > 0$ there is no time $f(k) \cdot N^{\gamma k}$ algorithm that can, given a $k$-ExactCover instance $I$, distinguish between the case where $I$ has an exact cover of size $k$ and the case where every set cover of $I$ has size at least $\frac14 \sqrt[k]{\frac{\log N}{\log \log N}}$. This rules out even more than FPT algorithms, and additionally rules out any algorithm whose approximation ratio depends only on the parameter $k$. By assuming SETH, we instead improve the lower bound to requiring time $f(k) \cdot N^{k - \varepsilon}$, for any $\varepsilon > 0$. #R##N#In this work we also extend the inapproximability result to the $k$-Nearest-Codeword ($k$-NCP) problem. Specifically, given a generator matrix $A \in \mathbb{F}_2^{m \times n}$, a vector $y \in \mathbb{F}_2^m$, and the parameter $k$, we show that it is hard to distinguish between the case where there exists a codeword with distance at most $k$ from $y$ and the case where every codeword has distance at least $\frac18 \sqrt[k]{\frac{\log N}{\log \log N}}$ from $y$. This improves the best known parameterized inapproximability result, which rules out approximations with a factor of $\text{poly} (\log k)$, but requires us to assume ETH instead of $W[1] \neq FPT$.

Connected through hyperedge HE-1 (induced by source paper "tight running time lower bounds for strong inapproximability of maximum k coverage unique set cover and related problems via t wise agreement testing theorem"):
  with members:
    - "a simple gap producing reduction for the parameterized set cover problem"
    - "parameterized intractability of even set and shortest vector problem"
    - "tight fpt approximations for k median and k means"
    - "agreement testing theorems on layered set systems"
    - "towards a general direct product testing theorem"
    - "gap s eth hardness of svp"
    - "eth hardness of approximating 2 csps and directed steiner network"
    - "from gap eth to fpt inapproximability clique dominating set and more"

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)