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: "a deamortization approach for dynamic spanner and dynamic maximal matching"
  Abstract: Many dynamic graph algorithms have an amortized update time, rather than a stronger worst-case guarantee. But amortized data structures are not suitable for real-time systems, where each individual operation has to be executed quickly. For this reason, there exist many recent randomized results that aim to provide a guarantee stronger than amortized expected. The strongest possible guarantee for a randomized algorithm is that it is always correct (Las Vegas), and has high-probability worst-case update time, which gives a bound on the time for each individual operation that holds with high probability. #R##N#In this paper we present the first polylogarithmic high-probability worst-case time bounds for the dynamic spanner and the dynamic maximal matching problem. 1. For dynamic spanner, the only known $o(n)$ worst-case bounds were $O(n^{3/4})$ high-probability worst-case update time for maintaining a 3-spanner and $O(n^{5/9})$ for maintaining a 5-spanner. We give a $O(1)^k \log^3(n)$ high-probability worst-case time bound for maintaining a $(2k-1)$-spanner, which yields the first worst-case polylog update time for all constant $k$. (All the results above maintain the optimal tradeoff of stretch $2k-1$ and $\tilde{O}(n^{1+1/k})$ edges.) 2. For dynamic maximal matching, or dynamic $2$-approximate maximum matching, no algorithm with $o(n)$ worst-case time bound was known and we present an algorithm with $O(\log^5(n))$ high-probability worst-case time; similar worst-case bounds existed only for maintaining a matching that was $(2+\epsilon)$-approximate, and hence not maximal. #R##N#Our results are achieved using a new black-box reduction that converts any data structure with worst-case expected update time into one with a high-probability worst-case update time: the query time remains the same, while the update time increases by a factor of $O(\log^2(n))$.

Connected through hyperedge HE-1 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model"):
  with members:
    - "how fast can you update your mst dynamic algorithms for cluster computing"
    - "batch dynamic algorithms via parallel change propagation and applications to dynamic trees"
    - "parallel batch dynamic graph connectivity"
    - "dynamic algorithms for the massively parallel computation model"
    - "fully dynamic maximal independent set in expected poly log update time"
    - "a deterministic algorithm for the mst problem in constant rounds of congested clique"
    - "exponentially faster massively parallel maximal matching"
    - "parallel batch dynamic graphs algorithms and lower bounds"

Connected through hyperedge HE-2 (induced by source paper "independent sets of dynamic rectangles algorithms and experiments"):
  with members:
    - "online matching with general arrivals"
    - "fully dynamic maximal independent set in expected poly log update time"
    - "exploring semi automatic map labeling"
    - "fully dynamic maximal independent set with polylogarithmic update time"
    - "fully dynamic maximal independent set with sublinear update time"
    - "dynamic algorithms for graph coloring"
    - "on approximating maximum independent set of rectangles"
    - "interval scheduling and colorful independent sets"

Connected through hyperedge HE-3 (induced by source paper "graph spanners a tutorial review"):
  with members:
    - "near additive spanners and near exact hopsets a unified view"
    - "some general structure for extremal sparsification problems"
    - "weighted additive spanners"
    - "near additive spanners in low polynomial deterministic congest time"
    - "multi level graph sketches via single level solvers"
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "an fpt algorithm for minimum additive spanner problem"
    - "distributed construction of light networks"

Connected through hyperedge HE-4 (induced by source paper "rounding dynamic matchings against an adaptive adversary"):
  with members:
    - "decremental sssp in weighted digraphs faster and against an adaptive adversary"
    - "deterministic algorithms for decremental approximate shortest paths faster and simpler"
    - "tight bounds for online edge coloring"
    - "distributed weighted matching via randomized composable coresets"
    - "online matching with general arrivals"
    - "dynamic low stretch trees via dynamic low diameter decompositions"
    - "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
    - "towards a unified theory of sparsification for matching problems"

Connected through hyperedge HE-5 (induced by source paper "dynamic approximate shortest paths and beyond subquadratic and worst case update time"):
  with members:
    - "fully dynamic all pairs shortest paths improved worst case time and space bounds"
    - "dynamic matrix inverse improved algorithms and matching conditional lower bounds"
    - "sensitive distance and reachability oracles for large batch updates"
    - "towards tight approximation bounds for graph diameter and eccentricities"
    - "algorithms and hardness for diameter in dynamic graphs"
    - "diameter spanner eccentricity spanner and approximating extremal graph distances static dynamic and fault tolerant"
    - "deterministic partially dynamic single source shortest paths in weighted graphs"
    - "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time"

Connected through hyperedge HE-6 (induced by source paper "dynamic low stretch trees via dynamic low diameter decompositions"):
  with members:
    - "faster distributed shortest path approximations via shortcuts"
    - "expander decomposition and pruning faster stronger and simpler"
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "efficient algorithms for constructing very sparse spanners and emulators"
    - "fully dynamic minimum spanning forest with improved worst case update time"
    - "on fully dynamic graph sparsifiers"
    - "fully dynamic spanners with worst case update time"

Connected through hyperedge HE-7 (induced by source paper "a new deterministic algorithm for dynamic set cover"):
  with members:
    - "dynamic matrix inverse improved algorithms and matching conditional lower bounds"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
    - "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time"
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "deterministic fully dynamic approximate vertex cover and fractional matching in o 1 amortized update time"
    - "fully dynamic maximal matching in constant update time"
    - "new deterministic approximation algorithms for fully dynamic matching"

Connected through hyperedge HE-8 (induced by source paper "dynamic algorithms for the massively parallel computation model"):
  with members:
    - "fully dynamic maximal independent set with sublinear update time"
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "connected components at scale via local contractions"
    - "coresets meet edcs algorithms for matching and vertex cover on massive graphs"
    - "dynamic matching reducing integral algorithms to approximately maximal fractional algorithms"
    - "round compression for parallel matching algorithms"
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "massively parallel algorithms and hardness for single linkage clustering under ell_p distances"

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)