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 multiple orientability thresholds for random hypergraphs"
  Abstract: A k-uniform hypergraph H = (V, E) is called l-orientable if there is an assignment of each edge e is an element of E to one of its vertices v is an element of e such that no vertex is assigned more than l edges. Let H-n,H-m,H-k be a hypergraph, drawn uniformly at random from the set of all k-uniform hypergraphs with n vertices and m edges. In this paper we establish the threshold for the l-orientability of H-n,H-m,H-k for all k >= 3 and l >= 2, that is, we determine a critical quantity c(*)k,l such that with probability 1-o(1) the graph H-n,H-cn,(k) has an l-orientation if c   c(k,l)(*) . Our result has various applications, including sharp load thresholds for cuckoo hashing, load balancing with guaranteed maximum load, and massive parallel access to hard disk arrays.

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"
    - "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"
    - "a simple proof of threshold saturation for coupled scalar recursions"

Connected through hyperedge HE-2 (induced by source paper "dense peelable random uniform hypergraphs"):
  with members:
    - "fast scalable construction of minimal perfect hash functions"
    - "cache oblivious peeling of random hypergraphs"
    - "biff bloom filter codes fast error correction for large data sets"
    - "invertible bloom lookup tables"
    - "sharp load thresholds for cuckoo hashing"
    - "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:
    - "on the insertion time of random walk cuckoo hashing"
    - "a cuckoo hashing variant with improved memory utilization and insertion time"
    - "sharp load thresholds for cuckoo hashing"
    - "tight thresholds for cuckoo hashing via xorsat"

Connected through hyperedge HE-4 (induced by source paper "thresholds for extreme orientability"):
  with members:
    - "a new data layout for set intersection on gpus"
    - "tight thresholds for cuckoo hashing via xorsat"

Connected through hyperedge HE-5 (induced by source paper "cuckoo hashing with pages"):
  with members:
    - "sharp load thresholds for cuckoo hashing"
    - "backyard cuckoo hashing constant worst case operations with a succinct representation"
    - "tight thresholds for cuckoo hashing via xorsat"

Connected through hyperedge HE-6 (induced by source paper "a cuckoo hashing variant with improved memory utilization and insertion time"):
  with members:
    - "cuckoo hashing with pages"
    - "tight thresholds for cuckoo hashing via xorsat"
    - "efficient hashing with lookups in two memory accesses"

Connected through hyperedge HE-7 (induced by source paper "on the insertion time of cuckoo hashing"):
  with members:
    - "sharp load thresholds for cuckoo hashing"
    - "tight thresholds for cuckoo hashing via xorsat"

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.DM(Discrete Mathematics)