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: "the power of two choices with simple tabulation"
  Abstract: The power of two choices is a classic paradigm for load balancing when assigning $m$ balls to $n$ bins. When placing a ball, we pick two bins according to two hash functions $h_0$ and $h_1$, and place the ball in the least loaded bin. Assuming fully random hash functions, when $m=O(n)$, Azar et al.~[STOC'94] proved that the maximum load is $\lg \lg n + O(1)$ with high probability. #R##N#In this paper, we investigate the power of two choices when the hash functions $h_0$ and $h_1$ are implemented with simple tabulation, which is a very efficient hash function evaluated in constant time. Following their analysis of Cuckoo hashing [J.ACM'12], P\v{a}tra\c{s}cu and Thorup claimed that the expected maximum load with simple tabulation is $O(\lg\lg n)$. This did not include any high probability guarantee, so the load balancing was not yet to be trusted. #R##N#Here, we show that with simple tabulation, the maximum load is $O(\lg\lg n)$ with high probability, giving the first constant time hash function with this guarantee. We also give a concrete example where, unlike with fully random hashing, the maximum load is not bounded by $\lg \lg n + O(1)$, or even $(1+o(1))\lg \lg n$ with high probability. Finally, we show that the expected maximum load is $\lg \lg n + O(1)$, just like with fully random hashing.

Connected through hyperedge HE-1 (induced by source paper "fast and powerful hashing using tabulation"):
  with members:
    - "from independence to expansion and back again"
    - "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"

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)