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: "parallel shortest paths using radius stepping"
  Abstract: The single-source shortest path problem (SSSP) with nonnegative edge weights is a notoriously difficult problem to solve efficiently in parallel---it is one of the graph problems said to suffer from the transitive-closure bottleneck. In practice, the $\Delta$-stepping algorithm of Meyer and Sanders (J. Algorithms, 2003) often works efficiently but has no known theoretical bounds on general graphs. The algorithm takes a sequence of steps, each increasing the radius by a user-specified value $\Delta$. Each step settles the vertices in its annulus but can take $\Theta(n)$ substeps, each requiring $\Theta(m)$ work ($n$ vertices and $m$ edges). #R##N#In this paper, we describe Radius-Stepping, an algorithm with the best-known tradeoff between work and depth bounds for SSSP with nearly-linear ($\otilde(m)$) work. The algorithm is a $\Delta$-stepping-like algorithm but uses a variable instead of fixed-size increase in radii, allowing us to prove a bound on the number of steps. In particular, by using what we define as a vertex $k$-radius, each step takes at most $k+2$ substeps. Furthermore, we define a $(k, \rho)$-graph property and show that if an undirected graph has this property, then the number of steps can be bounded by $O(\frac{n}{\rho} \log \rho L)$, for a total of $O(\frac{kn}{\rho} \log \rho L)$ substeps, each parallel. We describe how to preprocess a graph to have this property. Altogether, Radius-Stepping takes $O((m+n\log n)\log \frac{n}{\rho})$ work and $O(\frac{n}{\rho}\log n \log (\rho{}L))$ depth per source after preprocessing. The preprocessing step can be done in $O(m\log n + n\rho^2)$ work and $O(\rho^2)$ depth or in $O(m\log n + n\rho^2\log n)$ work and $O(\rho\log \rho)$ depth, and adds no more than $O(n\rho)$ edges.

Connected through hyperedge HE-1 (induced by source paper "parallel approximate undirected shortest paths via low hop emulators"):
  with members:
    - "preconditioning for the geometric transportation problem"
    - "fast approximate shortest paths in the congested clique"
    - "brief announcement semi mapreduce meets congested clique"
    - "thorup zwick emulators are universally optimal hopsets"
    - "near optimal approximate shortest paths and transshipment in distributed and streaming models"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "an almost tight distributed algorithm for computing single source shortest paths"

Connected through hyperedge HE-2 (induced by source paper "efficient construction of directed hopsets and parallel approximate shortest paths"):
  with members:
    - "nearly work efficient parallel algorithm for digraph reachability"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "improved parallel algorithms for spanners and hopsets"

Connected through hyperedge HE-3 (induced by source paper "a parallel priority queue with fast updates for gpu architectures"):
  with members:
    - "gunrock a high performance graph processing library on the gpu"
    - "merge path a visually intuitive approach to parallel merging"

Connected through hyperedge HE-4 (induced by source paper "more parallelism in dijkstra s single source shortest path algorithm"):
  with members:
    - "removing sequential bottleneck of dijkstra s algorithm for the shortest path problem"

Connected through hyperedge HE-5 (induced by source paper "improved parallel cache oblivious algorithms for dynamic programming and linear algebra"):
  with members:
    - "persistent memory i o primitives"
    - "parallel write efficient algorithms and data structures for computational geometry"
    - "algorithmic building blocks for asymmetric memories"
    - "the parallel persistent memory model"
    - "resource oblivious sorting on multicores"
    - "implicit decomposition for write efficient connectivity algorithms"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "extending the nested parallel model to the nested dataflow model with provably efficient schedulers"

Connected through hyperedge HE-6 (induced by source paper "parallelism in randomized incremental algorithms"):
  with members:
    - "theoretically efficient parallel graph algorithms can be fast and scalable"
    - "efficient construction of probabilistic tree embeddings"
    - "parallel correlation clustering on big graphs"
    - "scalable influence estimation in continuous time diffusion networks"
    - "greedy sequential maximal independent set and matching are parallel on average"

Connected through hyperedge HE-7 (induced by source paper "a faster distributed single source shortest paths algorithm"):
  with members:
    - "a deterministic distributed algorithm for exact weighted all pairs shortest paths in tilde o n 3 2 rounds"
    - "faster distributed shortest path approximations via shortcuts"
    - "distributed exact shortest paths in sublinear time"
    - "improved distributed algorithms for exact shortest paths"
    - "a simple deterministic distributed mst algorithm with near optimal time and message complexities"
    - "distributed approximation of maximum independent set and maximum matching"
    - "near optimal approximate shortest paths and transshipment in distributed and streaming models"
    - "hopsets with constant hopbound and applications to approximate shortest paths"

Connected through hyperedge HE-8 (induced by source paper "near optimal approximate shortest paths and transshipment in distributed and streaming models"):
  with members:
    - "thorup zwick emulators are universally optimal hopsets"
    - "distributed exact shortest paths in sublinear time"
    - "improved distributed algorithms for exact shortest paths"
    - "further algebraic algorithms in the congested clique model and applications to graph theoretic problems"
    - "generalized preconditioning and network flow problems"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "algebraic methods in the congested clique"

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)