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: "short cycles via low diameter decompositions"
  Abstract: We present improved algorithms for short cycle decomposition of a graph. Short cycle decompositions were introduced in the recent work of Chu et al, and were used to make progress on several questions in graph sparsification. #R##N#For all constants $\delta \in (0,1]$, we give an $O(mn^\delta)$ time algorithm that, given a graph $G,$ partitions its edges into cycles of length $O(\log n)^\frac{1}{\delta}$, with $O(n)$ extra edges not in any cycle. This gives the first subquadratic, in fact almost linear time, algorithm achieving polylogarithmic cycle lengths. We also give an $m \cdot \exp(O(\sqrt{\log n}))$ time algorithm that partitions the edges of a graph into cycles of length $\exp(O(\sqrt{\log n} \log\log n))$, with $O(n)$ extra edges not in any cycle. This improves on the short cycle decomposition algorithms given in Chu et al in terms of all parameters, and is significantly simpler. #R##N#As a result, we obtain faster algorithms and improved guarantees for several problems in graph sparsification -- construction of resistance sparsifiers, graphical spectral sketches, degree preserving sparsifiers, and approximating the effective resistances of all edges.

Connected through hyperedge HE-1 (induced by source paper "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond"):
  with members:
    - "faster p norm minimizing flows via smoothed q norm problems"
    - "fast provably convergent irls algorithm for p norm linear regression"
    - "distributed edge connectivity in sublinear time"
    - "improved distributed expander decomposition and nearly optimal triangle enumeration"
    - "flows in almost linear time via adaptive preconditioning"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
    - "graph sparsification spectral sketches and faster resistance computation via short cycle decompositions"

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)