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: "from independence to expansion and back again"
  Abstract: We consider the following fundamental problems: (1) Constructing $k$-independent hash functions with a space-time tradeoff close to Siegel's lower bound. (2) Constructing representations of unbalanced expander graphs having small size and allowing fast computation of the neighbor function. It is not hard to show that these problems are intimately connected in the sense that a good solution to one of them leads to a good solution to the other one. In this paper we exploit this connection to present efficient, recursive constructions of $k$-independent hash functions (and hence expanders with a small representation). While the previously most efficient construction (Thorup, FOCS 2013) needed time quasipolynomial in Siegel's lower bound, our time bound is just a logarithmic factor from the lower bound.

Connected through hyperedge HE-1 (induced by source paper "algorithms for similarity search and pseudorandomness"):
  with members:
    - "hardness of approximate nearest neighbor search"
    - "fast locality sensitive hashing for approximate near neighbor search"
    - "fast similarity sketching"
    - "embedjoin efficient edit similarity joins via embeddings"
    - "optimal densification for fast and accurate minwise hashing"
    - "parameter free locality sensitive hashing for spherical range reporting"
    - "scalable and robust set similarity join"
    - "fast cross polytope locality sensitive hashing"

Connected through hyperedge HE-2 (induced by source paper "fast hashing with strong concentration bounds"):
  with members:
    - "optimal streaming and tracking distinct elements with high probability"
    - "faster 64 bit universal hashing using carry less multiplications"
    - "pseudorandomness via the discrete fourier transform"
    - "high speed hashing for integers and strings"
    - "generating k independent variables in constant time"
    - "hashing for statistics over k partitions"
    - "bottom k and priority sampling set similarity and subset sums with minimal independence"
    - "simple tabulation fast expanders double tabulation and high independence"

Connected through hyperedge HE-3 (induced by source paper "a simple hash class with strong randomness properties in graphs and hypergraphs"):
  with members:
    - "approximately minwise independence with twisted tabulation"
    - "parallel peeling algorithms"
    - "simple tabulation fast expanders double tabulation and high independence"
    - "on the k independence required by linear probing and minwise 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-4 (induced by source paper "fast and powerful hashing using tabulation"):
  with members:
    - "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"
    - "on the k independence required by linear probing and minwise 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:
    - "generating k independent variables in constant time"
    - "simple tabulation fast expanders double tabulation and high independence"
    - "on the k independence required by linear probing and minwise independence"
    - "the power of simple tabulation hashing"
    - "linear probing with constant independence"

Connected through hyperedge HE-6 (induced by source paper "hashing for statistics over k partitions"):
  with members:
    - "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"
    - "on the k independence required by linear probing and minwise 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"

Connected through hyperedge HE-7 (induced by source paper "the power of two choices with simple tabulation"):
  with members:
    - "hashing for statistics over k partitions"
    - "simple tabulation fast expanders double tabulation and high independence"

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)