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 bounds for testing forbidden order patterns"
  Abstract: A sequence $f\colon\{1,\dots,n\}\to\mathbb{R}$ contains a permutation $\pi$ of length $k$ if there exist $i_1<\dots<i_k$ such that, for all $x,y$, $f(i_x)<f(i_y)$ if and only if $\pi(x)<\pi(y)$; otherwise, $f$ is said to be $\pi$-free. In this work, we consider the problem of testing for $\pi$-freeness with one-sided error, continuing the investigation of [Newman et al., SODA'17]. #R##N#We demonstrate a surprising behavior for non-adaptive tests with one-sided error: While a trivial sampling-based approach yields an $\varepsilon$-test for $\pi$-freeness making $\Theta(\varepsilon^{-1/k} n^{1-1/k})$ queries, our lower bounds imply that this is almost optimal for most permutations! Specifically, for most permutations $\pi$ of length $k$, any non-adaptive one-sided $\varepsilon$-test requires $\varepsilon^{-1/(k-\Theta(1))}n^{1-1/(k-\Theta(1))}$ queries; furthermore, the permutations that are hardest to test require $\Theta(\varepsilon^{-1/(k-1)}n^{1-1/(k-1)})$ queries, which is tight in $n$ and $\varepsilon$. #R##N#Additionally, we show two hierarchical behaviors here. First, for any $k$ and $l\leq k-1$, there exists some $\pi$ of length $k$ that requires $\tilde{\Theta}_{\varepsilon}(n^{1-1/l})$ non-adaptive queries. Second, we show an adaptivity hierarchy for $\pi=(1,3,2)$ by proving upper and lower bounds for (one- and two-sided) testing of $\pi$-freeness with $r$ rounds of adaptivity. The results answer open questions of Newman et al. and [Canonne and Gur, CCC'17].

Connected through hyperedge HE-1 (induced by source paper "optimal adaptive detection of monotone patterns"):
  with members:
    - "finding and counting permutations via csps"
    - "finding monotone patterns in sublinear time"
    - "adaptive lower bound for testing monotonicity on the line"
    - "testing local properties of arrays"
    - "adaptive boolean monotonicity testing in total influence time"
    - "beyond talagrand functions new lower bounds for testing monotonicity and unateness"
    - "boolean function monotonicity testing requires almost n 1 2 non adaptive queries"
    - "new algorithms and lower bounds for monotonicity testing"

Connected through hyperedge HE-2 (induced by source paper "finding monotone patterns in sublinear time"):
  with members:
    - "faster and simpler algorithms for finding large patterns in permutations"
    - "adaptive lower bound for testing monotonicity on the line"
    - "testing local properties of arrays"
    - "adaptive boolean monotonicity testing in total influence time"
    - "beyond talagrand functions new lower bounds for testing monotonicity and unateness"
    - "boolean function monotonicity testing requires almost n 1 2 non adaptive queries"
    - "new algorithms and lower bounds for monotonicity testing"
    - "finding small patterns in permutations in linear time"

Connected through hyperedge HE-3 (induced by source paper "counting small permutation patterns"):
  with members:
    - "faster and simpler algorithms for finding large patterns in permutations"
    - "finding and counting permutations via csps"
    - "finding small patterns in permutations in linear time"
    - "the computational landscape of permutation patterns"
    - "a fast algorithm for permutation pattern matching based on alternating runs"
    - "hereditary properties of permutations are strongly testable"
    - "orthogonal range searching on the ram revisited"

Connected through hyperedge HE-4 (induced by source paper "finding and counting permutations via csps"):
  with members:
    - "pattern avoiding access in binary search trees"
    - "hitting set for hypergraphs of low vc dimension"
    - "finding small patterns in permutations in linear time"
    - "the computational landscape of permutation patterns"
    - "a fast algorithm for permutation pattern matching based on alternating runs"

Connected through hyperedge HE-5 (induced by source paper "faster and simpler algorithms for finding large patterns in permutations"):
  with members:
    - "pattern avoiding access in binary search trees"
    - "finding small patterns in permutations in linear time"
    - "the computational landscape of permutation patterns"
    - "a fast algorithm for permutation pattern matching based on alternating runs"

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.DS(Data Structures and Algorithms)