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: "adapting sequential algorithms to the distributed setting"
  Abstract: It is a well known fact that sequential algorithms which exhibit a strong "local" nature can be adapted to the distributed setting given a legal graph coloring. The running time of the distributed algorithm will then be at least the number of colors. Surprisingly, this well known idea was never formally stated as a unified framework. In this paper we aim to define a robust family of local sequential algorithms which can be easily adapted to the distributed setting. We then develop new tools to further enhance these algorithms, achieving state of the art results for fundamental problems. #R##N#We define a simple class of greedy-like algorithms which we call \emph{orderless-local} algorithms. We show that given a legal $c$-coloring of the graph, every algorithm in this family can be converted into a distributed algorithm running in $O(c)$ communication rounds in the CONGEST model. We show that this family is indeed robust as both the method of conditional expectations and the unconstrained submodular maximization algorithm of Buchbinder \etal \cite{BuchbinderFNS15} can be expressed as orderless-local algorithms for \emph{local utility functions} --- Utility functions which have a strong local nature to them. #R##N#We use the above algorithms as a base for new distributed approximation algorithms for the weighted variants of some fundamental problems: Max $k$-Cut, Max-DiCut, Max 2-SAT and correlation clustering. We develop algorithms which have the same approximation guarantees as their sequential counterparts, up to a constant additive $\epsilon$ factor, while achieving an $O(\log^* n)$ running time for deterministic algorithms and $O(\epsilon^{-1})$ running time for randomized ones. This improves exponentially upon the currently best known algorithms.

Connected through hyperedge HE-1 (induced by source paper "hardness of distributed optimization"):
  with members:
    - "small cuts and connectivity certificates a fault tolerant approach"
    - "fast and efficient distributed computation of hamiltonian cycles in random graphs"
    - "a distributed algorithm for finding hamiltonian cycles in random graphs in o log n time"
    - "new distributed algorithms in almost mixing time via transformations from parallel algorithms"
    - "parameterized distributed algorithms"
    - "distributed exact weighted all pairs shortest paths in near linear time"
    - "detecting cliques in congest networks"
    - "simple and local independent set approximation"

Connected through hyperedge HE-2 (induced by source paper "fast and simple deterministic algorithms for highly dynamic networks"):
  with members:
    - "lower bounds for maximal matchings and maximal independent sets"
    - "how much does randomness help with locally checkable problems"
    - "simple dynamic algorithms for maximal independent set and other problems"
    - "fully dynamic maximal independent set with sublinear update time"
    - "local distributed algorithms in highly dynamic networks"
    - "improved algorithms for fully dynamic maximal independent set"
    - "improved deterministic distributed matching via rounding"
    - "new classes of distributed time complexity"

Connected through hyperedge HE-3 (induced by source paper "faster deterministic distributed coloring through recursive list coloring"):
  with members:
    - "towards the locality of vizing s theorem"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "improved distributed delta coloring"
    - "the complexity of distributed edge coloring with small palettes"
    - "deterministic distributed edge coloring with fewer colors"
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "on derandomizing local distributed algorithms"
    - "polynomial lower bound for distributed graph coloring in a weak local model"

Connected through hyperedge HE-4 (induced by source paper "efficient deterministic distributed coloring with small bandwidth"):
  with members:
    - "faster deterministic distributed coloring through recursive list coloring"
    - "on the use of randomness in local distributed graph algorithms"
    - "deterministic distributed dominating set approximation in the congest model"
    - "delta 1 coloring in the congested clique model"
    - "local distributed algorithms in highly dynamic networks"
    - "the complexity of delta 1 coloring incongested clique massively parallel computation and centralized local computation"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "on derandomizing local distributed algorithms"

Connected through hyperedge HE-5 (induced by source paper "deterministic distributed dominating set approximation in the congest model"):
  with members:
    - "delta 1 coloring in the congested clique model"
    - "congested clique algorithms for graph spanners"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "locally iterative distributed delta 1 coloring below szegedy vishwanathan barrier and applications to self stabilization and to restricted bandwidth models"
    - "on derandomizing local distributed algorithms"
    - "derandomizing local distributed algorithms under bandwidth restrictions"
    - "on the complexity of local distributed graph problems"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"

Connected through hyperedge HE-6 (induced by source paper "distributed approximation algorithms for maximum matching in graphs and hypergraphs"):
  with members:
    - "distributed dense subgraph detection and low outdegree orientation"
    - "polylogarithmic time deterministic network decomposition and distributed derandomization"
    - "lower bounds for maximal matchings and maximal independent sets"
    - "parameterized distributed algorithms"
    - "improved deterministic distributed matching via rounding"
    - "deterministic distributed edge coloring with fewer colors"
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "on derandomizing local distributed algorithms"

Connected through hyperedge HE-7 (induced by source paper "delta 1 coloring in the congested clique model"):
  with members:
    - "sublogarithmic distributed algorithms for lov asz local lemma and the complexity hierarchy"
    - "new classes of distributed time complexity"
    - "a time hierarchy theorem for the local model"
    - "an optimal distributed delta 1 coloring algorithm"
    - "derandomizing local distributed algorithms under bandwidth restrictions"
    - "an exponential separation between randomized and deterministic complexity in the local model"
    - "on the complexity of local distributed graph problems"
    - "local conflict coloring"

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.DC(Distributed, Parallel, and Cluster Computing)