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: "an optimal lower bound for monotonicity testing over hypergrids"
  Abstract: For positive integers $n, d$, consider the hypergrid $[n]^d$ with the coordinate-wise product partial ordering denoted by $\prec$. A function $f: [n]^d \mapsto \mathbb{N}$ is monotone if $\forall x \prec y$, $f(x) \leq f(y)$. A function $f$ is $\eps$-far from monotone if at least an $\eps$-fraction of values must be changed to make $f$ monotone. Given a parameter $\eps$, a \emph{monotonicity tester} must distinguish with high probability a monotone function from one that is $\eps$-far. #R##N#We prove that any (adaptive, two-sided) monotonicity tester for functions $f:[n]^d \mapsto \mathbb{N}$ must make $\Omega(\eps^{-1}d\log n - \eps^{-1}\log \eps^{-1})$ queries. Recent upper bounds show the existence of $O(\eps^{-1}d \log n)$ query monotonicity testers for hypergrids. This closes the question of monotonicity testing for hypergrids over arbitrary ranges. The previous best lower bound for general hypergrids was a non-adaptive bound of $\Omega(d \log n)$.

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 "approximating the distance to monotonicity of boolean functions"):
  with members:
    - "testing unateness nearly optimally"
    - "junta correlation is testable"
    - "lower bounds for tolerant junta and unateness testing via rejection sampling of graphs"
    - "beyond talagrand functions new lower bounds for testing monotonicity and unateness"
    - "settling the query complexity of non adaptive junta testing"
    - "optimal unateness testers for real valued functions adaptivity helps"
    - "tolerant junta testing and the connection to submodular optimization and function isomorphism"
    - "boolean function monotonicity testing requires almost n 1 2 non adaptive queries"

Connected through hyperedge HE-3 (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-4 (induced by source paper "towards testing monotonicity of distributions over general posets"):
  with members:
    - "optimal testing for properties of distributions"
    - "big data on the rise testing monotonicity of distributions"
    - "a polynomial lower bound for testing monotonicity"
    - "testing shape restrictions of discrete distributions"
    - "minimax rates of entropy estimation on large alphabets via best polynomial approximation"
    - "optimal bounds for monotonicity and lipschitz testing over hypercubes and hypergrids"
    - "learning k modal distributions via testing"
    - "testing k modal distributions optimal algorithms via reductions"

Connected through hyperedge HE-5 (induced by source paper "testing convexity of functions over finite domains"):
  with members:
    - "adaptive lower bound for testing monotonicity on the line"
    - "testing local properties of arrays"
    - "optimal bounds for monotonicity and lipschitz testing over hypercubes and hypergrids"
    - "is submodularity testable"

Connected through hyperedge HE-6 (induced by source paper "domain reduction for monotonicity testing a o d tester for boolean functions in d dimensions"):
  with members:
    - "is your function low dimensional"
    - "beyond talagrand functions new lower bounds for testing monotonicity and unateness"
    - "a polynomial lower bound for testing monotonicity"
    - "property testing on product distributions optimal testers for bounded derivative properties"
    - "new algorithms and lower bounds for monotonicity testing"
    - "optimal bounds for monotonicity and lipschitz testing over hypercubes and hypergrids"

Connected through hyperedge HE-7 (induced by source paper "adaptive lower bound for testing monotonicity on the line"):
  with members:
    - "beyond talagrand functions new lower bounds for testing monotonicity and unateness"
    - "a polynomial lower bound for testing monotonicity"
    - "boolean function monotonicity testing requires almost n 1 2 non adaptive queries"
    - "new algorithms and lower bounds for monotonicity testing"
    - "a o n monotonicity tester for boolean functions over the hypercube"
    - "optimal bounds for monotonicity and lipschitz testing over hypercubes and hypergrids"

Connected through hyperedge HE-8 (induced by source paper "boolean unateness testing with widetilde o n 3 4 adaptive queries"):
  with members:
    - "a lower bound for nonadaptive one sided error testing of unateness of boolean functions over the hypercube"
    - "an adaptivity hierarchy theorem for property testing"
    - "beyond talagrand functions new lower bounds for testing monotonicity and unateness"
    - "optimal unateness testers for real valued functions adaptivity helps"
    - "testing unateness of real valued functions"
    - "a widetilde o n non adaptive tester for unateness"
    - "a polynomial lower bound for testing monotonicity"
    - "boolean function monotonicity testing requires almost n 1 2 non adaptive queries"

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)