human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "how bandwidth affects the congest model"):
  Abstract: The $CONGEST$ model for distributed network computing is well suited for analyzing the impact of limiting the throughput of a network on its capacity to solve tasks efficiently. For many "global" problems there exists a lower bound of $\Omega(D + \sqrt{n/B})$, where $B$ is the amount of bits that can be exchanged between two nodes in one round of communication, $n$ is the number of nodes and $D$ is the diameter of the graph. Typically, upper bounds are given only for the case $B=O(\log n)$, or for the case $B = +\infty$. For $B=O(\log n)$, the Minimum Spanning Tree (MST) construction problem can be solved in $O(D + \sqrt{n}\log^* n)$ rounds, and the Single Source Shortest Path (SSSP) problem can be $(1+\epsilon)$-approximated in $\widetilde{O}(\epsilon^{-O(1)} (D+\sqrt{n}) )$ rounds. We extend these results by providing algorithms with a complexity parametric on $B$. We show that, for any $B=\Omega(\log n)$, there exists an algorithm that constructs a MST in $\widetilde{O}(D + \sqrt{n/B})$ rounds, and an algorithm that $(1+\epsilon)$-approximate the SSSP problem in $\widetilde{O}(\epsilon^{-O(1)} (D+\sqrt{n/B}) )$ rounds. We also show that there exist problems that are bandwidth insensitive.

Includes members:
  Member "approximate undirected transshipment and shortest paths via gradient descent":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed exact shortest paths in sublinear time")
  Member "distributed approximation algorithms for weighted shortest paths":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed edge connectivity in sublinear time")

Question: Please tell me which class the source paper 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.DC(Distributed, Parallel, and Cluster Computing)