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: "on the k independence required by linear probing and minwise independence"
  Abstract: We show that linear probing requires 5-independent hash functions for expected constant-time performance, matching an upper bound of [Pagh et al. STOC'07]. More precisely, we construct a 4-independent hash functions yielding expected logarithmic search time. #R##N#For (1+{\epsilon})-approximate minwise independence, we show that \Omega(log 1/{\epsilon})-independent hash functions are required, matching an upper bound of [Indyk, SODA'99]. #R##N#We also show that the very fast 2-independent multiply-shift scheme of Dietzfelbinger [STACS'96] fails badly in both applications.

Connected through hyperedge HE-1 (induced by source paper "secretary ranking with minimal inversions"):
  with members:
    - "active ranking from pairwise comparisons and when parametric assumptions don t help"
    - "top k ranking from pairwise comparisons when spectral ranking is optimal"
    - "parallel algorithms for select and partition with noisy comparisons"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "secretary problems with non uniform arrival order"
    - "spectral mle top k rank aggregation from pairwise comparisons"
    - "pricing online decisions beyond auctions"
    - "simple robust and optimal ranking from pairwise comparisons"

Connected through hyperedge HE-2 (induced by source paper "a simple hash class with strong randomness properties in graphs and hypergraphs"):
  with members:
    - "from independence to expansion and back again"
    - "approximately minwise independence with twisted tabulation"
    - "parallel peeling algorithms"
    - "simple tabulation fast expanders double tabulation and high independence"
    - "independence of tabulation based hash classes"
    - "on the insertion time of cuckoo hashing"
    - "tight thresholds for cuckoo hashing via xorsat"

Connected through hyperedge HE-3 (induced by source paper "exact weighted minwise hashing in constant time"):
  with members:
    - "consistent weighted sampling made fast small and easy"

Connected through hyperedge HE-4 (induced by source paper "fast and powerful hashing using tabulation"):
  with members:
    - "from independence to expansion and back again"
    - "the power of two choices with simple tabulation"
    - "generating k independent variables in constant time"
    - "approximately minwise independence with twisted tabulation"
    - "hashing for statistics over k partitions"
    - "simple tabulation fast expanders double tabulation and high independence"
    - "invertible bloom lookup tables"
    - "ams without 4 wise independence on product domains"

Connected through hyperedge HE-5 (induced by source paper "quicksort largest bucket and min wise hashing with limited independence"):
  with members:
    - "from independence to expansion and back again"
    - "generating k independent variables in constant time"
    - "simple tabulation fast expanders double tabulation and high independence"
    - "the power of simple tabulation hashing"
    - "linear probing with constant independence"

Connected through hyperedge HE-6 (induced by source paper "more analysis of double hashing for balanced allocations"):
  with members:
    - "balanced allocations a simple proof for the heavily loaded case"
    - "balanced allocations and double hashing"
    - "fast pseudo random fingerprints"

Connected through hyperedge HE-7 (induced by source paper "linear probing with 5 independent hashing"):
  with members:
    - "approximately minwise independence with twisted tabulation"
    - "bottom k and priority sampling set similarity and subset sums with minimal independence"

Connected through hyperedge HE-8 (induced by source paper "hashing for statistics over k partitions"):
  with members:
    - "from independence to expansion and back again"
    - "beyond locality sensitive hashing"
    - "all distances sketches revisited hip estimators for massive graphs analysis"
    - "bottom k and priority sampling set similarity and subset sums with minimal independence"
    - "simple tabulation fast expanders double tabulation and high independence"
    - "biff bloom filter codes fast error correction for large data sets"
    - "invertible bloom lookup tables"
    - "hyperanf approximating the neighbourhood function of very large graphs on a budget"

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)