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: "sharp load thresholds for cuckoo hashing"
  Abstract: The paradigm of many choices has influenced significantly the design of efficient data structures and, most notably, hash tables. Cuckoo hashing is a technique that extends this concept. There,we are given a table with $n$ locations, and we assume that each location can hold one item. Each item to be inserted chooses randomly k>1 locations and has to be placed in any one of them. How much load can cuckoo hashing handle before collisions prevent the successful assignment of the available items to the chosen locations? Practical evaluations of this method have shown that one can allocate a number of elements that is a large proportion of the size of the table, being very close to 1 even for small values of k such as 4 or 5. #R##N#In this paper we show that there is a critical value for this proportion: with high probability, when the amount of available items is below this value, then these can be allocated successfully, but when it exceeds this value, the allocation becomes impossible. We give explicitly for each k>1 this critical value. This answers an open question posed by Mitzenmacher (ESA '09) and underpins theoretically the experimental results. Our proofs are based on the translation of the question into a hypergraph setting, and the study of the related typical properties of random k-uniform hypergraphs.

Connected through hyperedge HE-1 (induced by source paper "peeling close to the orientability threshold spatial coupling in hashing based data structures"):
  with members:
    - "dense peelable random uniform hypergraphs"
    - "fast scalable construction of minimal perfect hash functions"
    - "bubing massive crawling for the masses"
    - "the multiple orientability thresholds for random hypergraphs"
    - "on the insertion time of random walk cuckoo hashing"
    - "high speed hashing for integers and strings"
    - "cache oblivious peeling of random hypergraphs"
    - "thresholds of spatially coupled systems via lyapunov s method"

Connected through hyperedge HE-2 (induced by source paper "dense peelable random uniform hypergraphs"):
  with members:
    - "fast scalable construction of minimal perfect hash functions"
    - "the multiple orientability thresholds for random hypergraphs"
    - "cache oblivious peeling of random hypergraphs"
    - "biff bloom filter codes fast error correction for large data sets"
    - "invertible bloom lookup tables"
    - "bloomier filters a second look"
    - "straggler identification in round trip data streams via newton s identities and invertible bloom filters"

Connected through hyperedge HE-3 (induced by source paper "load thresholds for cuckoo hashing with overlapping blocks"):
  with members:
    - "the multiple orientability thresholds for random hypergraphs"
    - "on the insertion time of random walk cuckoo hashing"
    - "a cuckoo hashing variant with improved memory utilization and insertion time"
    - "tight thresholds for cuckoo hashing via xorsat"

Connected through hyperedge HE-4 (induced by source paper "horcrux a password manager for paranoids"):
  with members:
    - "on the insertion time of cuckoo hashing"

Connected through hyperedge HE-5 (induced by source paper "fast scalable construction of minimal perfect hash functions"):
  with members:
    - "fast prefix search in little space with applications"
    - "bubing massive crawling for the masses"
    - "cache oblivious peeling of random hypergraphs"
    - "satisfiability thresholds beyond k xorsat"
    - "tight thresholds for cuckoo hashing via xorsat"

Connected through hyperedge HE-6 (induced by source paper "a faster algorithm for cuckoo insertion and bipartite matching in large graphs"):
  with members:
    - "a simple hash class with strong randomness properties in graphs and hypergraphs"
    - "on the insertion time of cuckoo hashing"
    - "de amortized cuckoo hashing provable worst case performance and experimental results"

Connected through hyperedge HE-7 (induced by source paper "the multiple orientability thresholds for random hypergraphs"):
  with members:
    - "tight thresholds for cuckoo hashing via xorsat"

Connected through hyperedge HE-8 (induced by source paper "on the insertion time of random walk cuckoo hashing"):
  with members:
    - "on the insertion time of cuckoo hashing"

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)