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: "an improved distributed algorithm for maximal independent set"
  Abstract: The Maximal Independent Set (MIS) problem is one of the basics in the study of locality in distributed graph algorithms. This paper presents an extremely simple randomized algorithm providing a near-optimal local complexity for this problem, which incidentally, when combined with some recent techniques, also leads to a near-optimal global complexity. #R##N#Classical algorithms of Luby [STOC'85] and Alon, Babai and Itai [JALG'86] provide the global complexity guarantee that, with high probability, all nodes terminate after $O(\log n)$ rounds. In contrast, our initial focus is on the local complexity, and our main contribution is to provide a very simple algorithm guaranteeing that each particular node $v$ terminates after $O(\log \mathsf{deg}(v)+\log 1/\epsilon)$ rounds, with probability at least $1-\epsilon$. The guarantee holds even if the randomness outside $2$-hops neighborhood of $v$ is determined adversarially. This degree-dependency is optimal, due to a lower bound of Kuhn, Moscibroda, and Wattenhofer [PODC'04]. #R##N#Interestingly, this local complexity smoothly transitions to a global complexity: by adding techniques of Barenboim, Elkin, Pettie, and Schneider [FOCS'12, arXiv: 1202.1983v3], we get a randomized MIS algorithm with a high probability global complexity of $O(\log \Delta) + 2^{O(\sqrt{\log \log n})}$, where $\Delta$ denotes the maximum degree. This improves over the $O(\log^2 \Delta) + 2^{O(\sqrt{\log \log n})}$ result of Barenboim et al., and gets close to the $\Omega(\min\{\log \Delta, \sqrt{\log n}\})$ lower bound of Kuhn et al. #R##N#Corollaries include improved algorithms for MIS in graphs of upper-bounded arboricity, or lower-bounded girth, for Ruling Sets, for MIS in the Local Computation Algorithms (LCA) model, and a faster distributed algorithm for the Lov\'asz Local Lemma.

Connected through hyperedge HE-1 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples"):
  with members:
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "weighted matchings via unweighted augmentations"
    - "coresets meet edcs algorithms for matching and vertex cover on massive graphs"
    - "extractor based time space lower bounds for learning"
    - "estimating graph parameters from random order streams"
    - "testable bounded degree graph properties are random order streamable"
    - "on estimating maximum matching size in graph streams"
    - "a 2 ϵ approximation for maximum weight matching in the semi streaming model"

Connected through hyperedge HE-2 (induced by source paper "graph sparsification for derandomizing massively parallel computation with low space"):
  with members:
    - "walking randomly massively and efficiently"
    - "parallel approximate undirected shortest paths via low hop emulators"
    - "deterministic distributed dominating set approximation in the congest model"
    - "efficient deterministic distributed coloring with small bandwidth"
    - "exponentially faster massively parallel maximal matching"
    - "congested clique algorithms for graph spanners"
    - "massively parallel algorithms for finding well connected components in sparse graphs"
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"

Connected through hyperedge HE-3 (induced by source paper "distributed construction of light networks"):
  with members:
    - "light spanners for high dimensional norms via stochastic decompositions"
    - "greedy spanners are optimal in doubling metrics"
    - "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"
    - "constructing light spanners deterministically in near linear time"
    - "minor free graphs have light spanners"
    - "the greedy spanner is existentially optimal"

Connected through hyperedge HE-4 (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-5 (induced by source paper "a topological perspective on distributed network algorithms"):
  with members:
    - "topological characterization of consensus under general message adversaries"
    - "lower bounds for maximal matchings and maximal independent sets"
    - "why extension based proofs fail"
    - "tight bounds for asymptotic and approximate consensus"
    - "locally iterative distributed delta 1 coloring below szegedy vishwanathan barrier and applications to self stabilization and to restricted bandwidth models"
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "on the complexity of local distributed graph problems"
    - "gracefully degrading consensus and k set agreement in directed dynamic networks"

Connected through hyperedge HE-6 (induced by source paper "a sharp threshold phenomenon for the distributed complexity of the lovasz local lemma"):
  with members:
    - "on the complexity of distributed splitting problems"
    - "polylogarithmic time deterministic network decomposition and distributed derandomization"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "improved distributed degree splitting and edge coloring"
    - "a time hierarchy theorem for the local model"
    - "on derandomizing local distributed algorithms"
    - "distributed degree splitting edge coloring and orientations"
    - "an exponential separation between randomized and deterministic complexity in the local model"

Connected through hyperedge HE-7 (induced by source paper "on the use of randomness in local distributed graph algorithms"):
  with members:
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "on derandomizing local distributed algorithms"
    - "distributed degree splitting edge coloring and orientations"
    - "an exponential separation between randomized and deterministic complexity in the local model"
    - "on the complexity of local distributed graph problems"
    - "distributed strong diameter network decomposition"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"
    - "a lower bound for the distributed lov asz local lemma"

Connected through hyperedge HE-8 (induced by source paper "lower bounds for maximal matchings and maximal independent sets"):
  with members:
    - "an automatic speedup theorem for distributed problems"
    - "hardness of minimal symmetry breaking in distributed computing"
    - "the complexity of distributed edge coloring with small palettes"
    - "improved deterministic distributed matching via rounding"
    - "an exponential separation between randomized and deterministic complexity in the local model"
    - "local conflict coloring"
    - "a lower bound for the distributed lov asz local lemma"
    - "linear in delta lower bounds in the local model"

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)