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: "estimating the longest increasing sequence in polylogarithmic time"
  Abstract: Finding the length of the longest increasing subsequence (LIS) is a classic algorithmic problem. Let $n$ denote the size of the array. Simple $O(n\log n)$ algorithms are known for this problem. We develop a polylogarithmic time randomized algorithm that for any constant $\delta > 0$, estimates the length of the LIS of an array to within an additive error of $\delta n$. More precisely, the running time of the algorithm is $(\log n)^c (1/\delta)^{O(1/\delta)}$ where the exponent $c$ is independent of $\delta$. Previously, the best known polylogarithmic time algorithms could only achieve an additive $n/2$ approximation. With a suitable choice of parameters, our algorithm also gives, for any fixed $\tau>0$, a multiplicative $(1+\tau)$-approximation to the distance to monotonicity $\varepsilon_f$ (the fraction of entries not in the LIS), whose running time is polynomial in $\log(n)$ and $1/varepsilon_f$. The best previously known algorithm could only guarantee an approximation within a factor (arbitrarily close to) 2.

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"
    - "improved bounds for testing forbidden order patterns"
    - "boolean function monotonicity testing requires almost n 1 2 non adaptive queries"

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"
    - "improved bounds for testing forbidden order patterns"
    - "boolean function monotonicity testing requires almost n 1 2 non adaptive queries"
    - "new algorithms and lower bounds for monotonicity testing"

Connected through hyperedge HE-3 (induced by source paper "space efficient algorithms for longest increasing subsequence"):
  with members:
    - "improved time space trade offs for computing voronoi diagrams"
    - "on space efficiency of algorithms working on structural decompositions of graphs"
    - "space efficient streaming algorithms for the distance to monotonicity and asymmetric edit distance"

Connected through hyperedge HE-4 (induced by source paper "erasure resilient property testing"):
  with members:
    - "property testing on product distributions optimal testers for bounded derivative properties"
    - "an optimal lower bound for monotonicity testing over hypergrids"
    - "active property testing"
    - "testing closeness of discrete distributions"
    - "transitive closure spanners"

Connected through hyperedge HE-5 (induced by source paper "space efficient streaming algorithms for the distance to monotonicity and asymmetric edit distance"):
  with members:
    - "polylogarithmic approximation for edit distance and the asymmetric query complexity"
    - "transitive closure spanners"
    - "fast and compact regular expression matching"

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)