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: "sparse matrix multiplication with bandwidth restricted all to all communication"
  Abstract: We show how to multiply two $n \times n$ matrices over semirings in the Congested Clique model, where $n$ nodes synchronously communicate in an all-to-all manner using $O(\log n)$-bit messages, within a round complexity that depends on the number of non-zero elements in the input matrices. By leveraging the sparsity of the input matrices, our algorithm reduces communication costs and thus improves upon the state-of-the-art for matrices with $o(n^2)$ nonzero elements. Moreover, our algorithm exhibits the additional strength of surpassing previous solutions also in the case where only one of the two matrices is such. Particularly, this allows to efficiently raise a sparse matrix to a power greater than 2. #R##N#As applications, we show how to speed up the computation on non-dense graphs of 3- and 4-cycle counting, as well as of all-pairs-shortest-paths. #R##N#Our algorithmic contribution is a new deterministic method of restructuring the input matrices in a sparsity-aware manner, which assigns each node with element-wise multiplication tasks that are not necessarily consecutive but guarantee a balanced element distribution, providing for communication-efficient multiplication. As such, our technique may be useful in additional computational models.

Connected through hyperedge HE-1 (induced by source paper "simple graph coloring algorithms for congested clique and massively parallel computation"):
  with members:
    - "massively parallel algorithms for finding well connected components in sparse graphs"
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "improved massively parallel computation algorithms for mis matching and vertex cover"
    - "distributed symmetry breaking algorithms for congested cliques"
    - "breaking the linear memory barrier in mpc fast mis on trees with n e memory per machine"
    - "greedy and local ratio algorithms in the mapreduce model"
    - "mst in o 1 rounds of the congested clique"
    - "simple round compression for parallel vertex cover"

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)