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: "from gap eth to fpt inapproximability clique dominating set and more"
  Abstract: We consider questions that arise from the intersection between the areas of polynomial-time approximation algorithms, subexponential-time algorithms, and fixed-parameter tractable algorithms. The questions, which have been asked several times (e.g., [Marx08, FGMS12, DF13]), are whether there is a non-trivial FPT-approximation algorithm for the Maximum Clique (Clique) and Minimum Dominating Set (DomSet) problems parameterized by the size of the optimal solution. In particular, letting $\text{OPT}$ be the optimum and $N$ be the size of the input, is there an algorithm that runs in $t(\text{OPT})\text{poly}(N)$ time and outputs a solution of size $f(\text{OPT})$, for any functions $t$ and $f$ that are independent of $N$ (for Clique, we want $f(\text{OPT})=\omega(1)$)? #R##N#In this paper, we show that both Clique and DomSet admit no non-trivial FPT-approximation algorithm, i.e., there is no $o(\text{OPT})$-FPT-approximation algorithm for Clique and no $f(\text{OPT})$-FPT-approximation algorithm for DomSet, for any function $f$ (e.g., this holds even if $f$ is the Ackermann function). In fact, our results imply something even stronger: The best way to solve Clique and DomSet, even approximately, is to essentially enumerate all possibilities. Our results hold under the Gap Exponential Time Hypothesis (Gap-ETH) [Dinur16, MR16], which states that no $2^{o(n)}$-time algorithm can distinguish between a satisfiable 3SAT formula and one which is not even $(1 - \epsilon)$-satisfiable for some constant $\epsilon > 0$. #R##N#Besides Clique and DomSet, we also rule out non-trivial FPT-approximation for Maximum Balanced Biclique, Maximum Subgraphs with Hereditary Properties, and Maximum Induced Matching in bipartite graphs. Additionally, we rule out $k^{o(1)}$-FPT-approximation algorithm for Densest $k$-Subgraph although this ratio does not yet match the trivial $O(k)$-approximation algorithm.

Connected through hyperedge HE-1 (induced by source paper "parameterized inapproximability for steiner orientation by gap amplification"):
  with members:
    - "tight fpt approximations for k median and k means"
    - "constant factor fpt approximation for capacitated k median"
    - "faster exact and approximate algorithms for k cut"
    - "completely inapproximable monotone and antimonotone parameterized problems"
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "a birthday repetition theorem and complexity of approximating dense csps"
    - "directed multicut is w 1 hard even for four terminal pairs"
    - "the parameterized complexity of k biclique"

Connected through hyperedge HE-2 (induced by source paper "approximating subset sum is equivalent to min plus convolution"):
  with members:
    - "an improved fptas for 0 1 knapsack"
    - "approximating apsp without scaling equivalence of approximate min plus and exact min max"
    - "on problems equivalent to min convolution"
    - "subquadratic approximation scheme for partition"
    - "fast algorithms for knapsack via convolution and prediction"
    - "an equivalence class for orthogonal vectors"
    - "on integer programming and convolution"
    - "on the hardness of approximate and exact bichromatic maximum inner product"

Connected through hyperedge HE-3 (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"
    - "parameterized inapproximability of exact cover and nearest codeword"
    - "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"

Connected through hyperedge HE-4 (induced by source paper "approximating apsp without scaling equivalence of approximate min plus and exact min max"):
  with members:
    - "on problems equivalent to min convolution"
    - "subquadratic approximation scheme for partition"
    - "hardness of approximate nearest neighbor search"
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "distributed pcp theorems for hardness of approximation in p"
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "a fast numerical method for max convolution and the application to efficient max product inference in bayesian networks"

Connected through hyperedge HE-5 (induced by source paper "tight fpt approximations for k median and k means"):
  with members:
    - "turning big data into tiny data constant size coresets for k means pca and projective clustering"
    - "improved and simplified inapproximability for k means"
    - "the hardness of approximation of euclidean k means"
    - "the constant inapproximability of the parameterized dominating set problem"
    - "an improved approximation for k median and positive correlation in budgeted optimization"
    - "the parameterized complexity of k biclique"
    - "approximating k median via pseudo approximation"
    - "a unified framework for approximating and clustering data"

Connected through hyperedge HE-6 (induced by source paper "inapproximability within w 1 the case of steiner orientation"):
  with members:
    - "tight fpt approximations for k median and k means"
    - "constant factor fpt approximation for capacitated k median"
    - "faster exact and approximate algorithms for k cut"
    - "completely inapproximable monotone and antimonotone parameterized problems"
    - "directed multicut is w 1 hard even for four terminal pairs"
    - "the parameterized complexity of k biclique"
    - "steiner forest orientation problems"
    - "multicut is fpt"

Connected through hyperedge HE-7 (induced by source paper "approximation and hardness of shift bribery"):
  with members:
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "a birthday repetition theorem and complexity of approximating dense csps"
    - "prices matter for the parameterized complexity of shift bribery"
    - "campaign management under approval driven voting rules"
    - "the constant inapproximability of the parameterized dominating set problem"
    - "the complexity of probabilistic lobbying"
    - "how hard is bribery in elections"

Connected through hyperedge HE-8 (induced by source paper "a simple gap producing reduction for the parameterized set cover problem"):
  with members:
    - "distributed pcp theorems for hardness of approximation in p"
    - "the constant inapproximability of the parameterized dominating set problem"
    - "the parameterized complexity of k biclique"
    - "losing weight by gaining edges"
    - "exact weight subgraphs and the k sum conjecture"
    - "analytical approach to parallel repetition"

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)