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 unateness testers for real valued functions adaptivity helps"):
  Abstract: We study the problem of testing unateness of functions $f:\{0,1\}^d \to \mathbb{R}.$ We give a $O(\frac{d}{\epsilon} \cdot \log\frac{d}{\epsilon})$-query nonadaptive tester and a $O(\frac{d}{\epsilon})$-query adaptive tester and show that both testers are optimal for a fixed distance parameter $\epsilon$. Previously known unateness testers worked only for Boolean functions, and their query complexity had worse dependence on the dimension both for the adaptive and the nonadaptive case. Moreover, no lower bounds for testing unateness were known. We also generalize our results to obtain optimal unateness testers for functions $f:[n]^d \to \mathbb{R}$. #R##N#Our results establish that adaptivity helps with testing unateness of real-valued functions on domains of the form $\{0,1\}^d$ and, more generally, $[n]^d$. This stands in contrast to the situation for monotonicity testing where there is no adaptivity gap for functions $f:[n]^d \to \mathbb{R}$.

Includes members:
  Member "beyond talagrand functions new lower bounds for testing monotonicity and unateness":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "almost optimal testers for concise representations")
  Member "a polynomial lower bound for testing monotonicity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "almost optimal testers for concise representations")
  Member "property testing on product distributions optimal testers for bounded derivative properties":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "domain reduction for monotonicity testing a o d tester for boolean functions in d dimensions")
  Member "new algorithms and lower bounds for monotonicity testing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "almost optimal testers for concise representations")
  Member "an optimal lower bound for monotonicity testing over hypergrids":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal adaptive detection of monotone patterns")
  Member "optimal bounds for monotonicity and lipschitz testing over hypercubes and hypergrids":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal adaptive detection of monotone patterns")
  Member "transitive closure spanners":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "efficient and simple algorithms for fault tolerant spanners")

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)