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 "parameterized approximation schemes for independent set of rectangles and geometric knapsack"):
  Abstract: The area of parameterized approximation seeks to combine approximation and parameterized algorithms to obtain, e.g., (1+eps)-approximations in f(k,eps)n^{O(1)} time where k is some parameter of the input. We obtain the following results on parameterized approximability: 1) In the maximum independent set of rectangles problem (MISR) we are given a collection of n axis parallel rectangles in the plane. Our goal is to select a maximum-cardinality subset of pairwise non-overlapping rectangles. This problem is NP-hard and also W[1]-hard [Marx, ESA'05]. The best-known polynomial-time approximation factor is O(loglog n) [Chalermsook and Chuzhoy, SODA'09] and it admits a QPTAS [Adamaszek and Wiese, FOCS'13; Chuzhoy and Ene, FOCS'16]. Here we present a parameterized approximation scheme (PAS) for MISR, i.e. an algorithm that, for any given constant eps>0 and integer k>0, in time f(k,eps)n^{g(eps)}, either outputs a solution of size at least k/(1+eps), or declares that the optimum solution has size less than k. 2) In the (2-dimensional) geometric knapsack problem (TDK) we are given an axis-aligned square knapsack and a collection of axis-aligned rectangles in the plane (items). Our goal is to translate a maximum cardinality subset of items into the knapsack so that the selected items do not overlap. In the version of TDK with rotations (TDKR), we are allowed to rotate items by 90 degrees. Both variants are NP-hard, and the best-known polynomial-time approximation factors are 558/325+eps and 4/3+eps, resp. [Galvez et al., FOCS'17]. These problems admit a QPTAS for polynomially bounded item sizes [Adamaszek and Wiese, SODA'15]. We show that both variants are W[1]-hard. Furthermore, we present a PAS for TDKR. For all considered problems, getting time f(k,eps)n^{O(1)}, rather than f(k,eps)n^{g(eps)}, would give FPT time f'(k)n^{O(1)} exact algorithms using eps=1/(k+1), contradicting W[1]-hardness.

Includes members:
  Member "approximating geometric knapsack via l packings":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "breaking the barrier of 2 for the storage allocation problem")
  Member "on approximating maximum independent set of rectangles":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "independent sets of dynamic rectangles algorithms and experiments")
  Member "fixed parameter approximations for k center problems in low highway dimension graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "travelling on graphs with small highway dimension")
  Member "lower bounds for approximation schemes for closest string":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "low rank binary matrix approximation in column sum norm")
  Member "a fixed parameter tractable approximation scheme for the optimal cut graph of a surface":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "almost tight lower bounds for hard cutting problems in embedded graphs")
  Member "the constant inapproximability of the parameterized dominating set problem":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "trapping problem on star type graphs with applications")
  Member "parameterized approximability of maximizing the spread of influence in networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on influence maximization in a social network")
  Member "parameterized approximation schemes using graph widths":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "parameterized power vertex cover")

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)