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: "greedy is an almost optimal deque"
  Abstract: In this paper we extend the geometric binary search tree (BST) model of Demaine, Harmon, Iacono, Kane, and Patrascu (DHIKP) to accommodate for insertions and deletions. Within this extended model, we study the online Greedy BST algorithm introduced by DHIKP. Greedy BST is known to be equivalent to a maximally greedy (but inherently offline) algorithm introduced independently by Lucas in 1988 and Munro in 2000, conjectured to be dynamically optimal. #R##N#With the application of forbidden-submatrix theory, we prove a quasilinear upper bound on the performance of Greedy BST on deque sequences. It has been conjectured (Tarjan, 1985) that splay trees (Sleator and Tarjan, 1983) can serve such sequences in linear time. Currently neither splay trees, nor other general-purpose BST algorithms are known to fulfill this requirement. As a special case, we show that Greedy BST can serve output-restricted deque sequences in linear time. A similar result is known for splay trees (Tarjan, 1985; Elmasry, 2004). #R##N#As a further application of the insert-delete model, we give a simple proof that, given a set U of permutations of [n], the access cost of any BST algorithm is Omega(log |U| + n) on "most" of the permutations from U. In particular, this implies that the access cost for a random permutation of [n] is Omega(n log n) with high probability. #R##N#Besides the splay tree noted before, Greedy BST has recently emerged as a plausible candidate for dynamic optimality. Compared to splay trees, much less effort has gone into analyzing Greedy BST. Our work is intended as a step towards a full understanding of Greedy BST, and we remark that forbidden-submatrix arguments seem particularly well suited for carrying out this program.

Connected through hyperedge HE-1 (induced by source paper "pinning down the strong wilber 1 bound for binary search trees"):
  with members:
    - "settling the relationship between wilber s bounds for dynamic optimality"
    - "pattern avoiding access in binary search trees"
    - "splay trees davenport schinzel sequences and the deque conjecture"

Connected through hyperedge HE-2 (induced by source paper "smooth heaps and a dual view of self adjusting data structures"):
  with members:
    - "weighted dynamic finger in binary search trees"
    - "improved bounds for multipass pairing heaps and path balanced binary search trees"
    - "pairing heaps the forward variant"
    - "the landscape of bounds for binary search trees"
    - "pattern avoiding access in binary search trees"
    - "a back to basics empirical study of priority queues"
    - "a tight lower bound for decrease key in the pure heap model"
    - "finding small patterns in permutations in linear time"

Connected through hyperedge HE-3 (induced by source paper "pattern avoiding access in binary search trees"):
  with members:
    - "self adjusting binary search trees what makes them tick"
    - "combining binary search trees"
    - "the computational landscape of permutation patterns"
    - "in pursuit of the dynamic optimality conjecture"
    - "upper bounds for maximally greedy binary search trees"
    - "improved bounds and new techniques for davenport schinzel sequences and their generalizations"
    - "splay trees davenport schinzel sequences and the deque conjecture"

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)