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: "on the complexity of local distributed graph problems"
  Abstract: This paper is centered on the complexity of graph problems in the well-studied LOCAL model of distributed computing, introduced by Linial [FOCS '87]. It is widely known that for many of the classic distributed graph problems (including maximal independent set (MIS) and $(\Delta+1)$-vertex coloring), the randomized complexity is at most polylogarithmic in the size $n$ of the network, while the best deterministic complexity is typically $2^{O(\sqrt{\log n})}$. Understanding and narrowing down this exponential gap is considered to be one of the central long-standing open questions in the area of distributed graph algorithms. We investigate the problem by introducing a complexity-theoretic framework that allows us to shed some light on the role of randomness in the LOCAL model. We define the SLOCAL model as a sequential version of the LOCAL model. Our framework allows us to prove completeness results with respect to the class of problems which can be solved efficiently in the SLOCAL model, implying that if any of the complete problems can be solved deterministically in $\log^{O(1)} n$ rounds in the LOCAL model, we can deterministically solve all efficient SLOCAL-problems (including MIS and $(\Delta+1)$-coloring) in $\log^{O(1)} n$ rounds in the LOCAL model. We show that a rather rudimentary looking graph coloring problem is complete in the above sense: Color the nodes of a graph with colors red and blue such that each node of sufficiently large polylogarithmic degree has at least one neighbor of each color. The problem admits a trivial zero-round randomized solution. The result can be viewed as showing that the only obstacle to getting efficient determinstic algorithms in the LOCAL model is an efficient algorithm to approximately round fractional values into integer values.

Connected through hyperedge HE-1 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta"):
  with members:
    - "faster deterministic distributed coloring through recursive list coloring"
    - "polylogarithmic time deterministic network decomposition and distributed derandomization"
    - "towards the locality of vizing s theorem"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "a breezing proof of the kmw bound"):
  with members:
    - "lower bounds for maximal matchings and maximal independent sets"
    - "the complexity of distributed edge coloring with small palettes"
    - "a hierarchy of local decision"
    - "a lower bound for the distributed lov asz local lemma"
    - "lower bounds for local approximation"
    - "local computation lower and upper bounds"

Connected through hyperedge HE-3 (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-4 (induced by source paper "broadcast congested clique planted cliques and pseudorandom generators"):
  with members:
    - "congested clique algorithms for graph spanners"
    - "optimal lower bounds for distributed and streaming spanning forest computation"
    - "msf and connectivity in limited variants of the congested clique"
    - "a time hierarchy theorem for the local model"
    - "on derandomizing local distributed algorithms"
    - "deterministic subgraph detection in broadcast congest"
    - "towards a complexity theory for the congested clique"
    - "deterministic graph connectivity in the broadcast congested clique"

Connected through hyperedge HE-5 (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-6 (induced by source paper "classification of distributed binary labeling problems"):
  with members:
    - "seeing far vs seeing wide volume complexity of local graph problems"
    - "an automatic speedup theorem for distributed problems"
    - "polylogarithmic time deterministic network decomposition and distributed derandomization"
    - "lower bounds for maximal matchings and maximal independent sets"
    - "how much does randomness help with locally checkable problems"
    - "almost global problems in the local model"
    - "the distributed complexity of locally checkable problems on paths is decidable"
    - "hardness of minimal symmetry breaking in distributed computing"

Connected through hyperedge HE-7 (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"
    - "adapting sequential algorithms to the distributed setting"
    - "on derandomizing local distributed algorithms"

Connected through hyperedge HE-8 (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"
    - "adapting sequential algorithms to the distributed setting"

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)