human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "optimal adaptive detection of monotone patterns"):
  Abstract: We investigate adaptive sublinear algorithms for detecting monotone patterns in an array. Given fixed $2 \leq k \in \mathbb{N}$ and $\varepsilon > 0$, consider the problem of finding a length-$k$ increasing subsequence in an array $f \colon [n] \to \mathbb{R}$, provided that $f$ is $\varepsilon$-far from free of such subsequences. Recently, it was shown that the non-adaptive query complexity of the above task is $\Theta((\log n)^{\lfloor \log_2 k \rfloor})$. In this work, we break the non-adaptive lower bound, presenting an adaptive algorithm for this problem which makes $O(\log n)$ queries. This is optimal, matching the classical $\Omega(\log n)$ adaptive lower bound by Fischer [2004] for monotonicity testing (which corresponds to the case $k=2$), and implying in particular that the query complexity of testing whether the longest increasing subsequence (LIS) has constant length is $\Theta(\log n)$.

Includes members:
  Member "finding and counting permutations via csps":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "counting small permutation patterns")
  Member "finding monotone patterns in sublinear time":
    also connected through other hyperedges:
      (none)
  Member "adaptive lower bound for testing monotonicity on the line":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "finding monotone patterns in sublinear time")
  Member "testing local properties of arrays":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "finding monotone patterns in sublinear time")
  Member "adaptive boolean monotonicity testing in total influence time":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "finding monotone patterns in sublinear time")
  Member "beyond talagrand functions new lower bounds for testing monotonicity and unateness":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "almost optimal testers for concise representations")
  Member "improved bounds for testing forbidden order patterns":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "finding monotone patterns in sublinear time")
  Member "boolean function monotonicity testing requires almost n 1 2 non adaptive queries":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "almost optimal testers for concise representations")

Question: Please tell me which class the source paper 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)