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: "deterministic parameterized connected vertex cover"
  Abstract: In the Connected Vertex Cover problem we are given an undirected graph G together with an integer k and we are to find a subset of vertices X of size at most k, such that X contains at least one end-point of each edge and moreover X induces a connected subgraph. For this problem we present a deterministic algorithm running in O(2^k n^O(1)) time and polynomial space, improving over previously best O(2.4882^k n^O(1)) deterministic algorithm and O(2^k n^O(1)) randomized algorithm. Furthermore, when usage of exponential space is allowed, we present an O(2^k k(n+m)) time algorithm that solves a more general variant with arbitrary real weights. #R##N#Finally, we show that in O(2k k(n + m)) time and O(2^k k) space one can count the number of connected vertex covers of size at most k, which can not be improved to O((2 - eps)^k nO(1)) for any eps > 0 under the Strong Exponential Time Hypothesis, as shown by Cygan et al. [CCC'12].

Connected through hyperedge HE-1 (induced by source paper "parameterized algorithms for maximum cut with connectivity constraints"):
  with members:
    - "weighted upper edge cover complexity and approximability"
    - "a linear time algorithm for a variant of the max cut problem in series parallel graphs"
    - "approximation algorithms for connected maximum cut and related problems"
    - "solving connectivity problems parameterized by treewidth in single exponential time"

Connected through hyperedge HE-2 (induced by source paper "revisiting connected vertex cover fpt algorithms and lossy kernels"):
  with members:
    - "on problems as hard as cnf sat"
    - "data reduction for graph coloring problems"
    - "kernelization lower bounds by cross composition"
    - "faster parameterized algorithms using linear programming"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"

Connected through hyperedge HE-3 (induced by source paper "reoptimization of parameterized problems"):
  with members:
    - "dynamic parameterized problems and algorithms"
    - "on finding directed trees with many leaves"
    - "a linear vertex kernel for maximum internal spanning tree"

Connected through hyperedge HE-4 (induced by source paper "parameterized power vertex cover"):
  with members:
    - "parameterized approximation schemes using graph widths"

Connected through hyperedge HE-5 (induced by source paper "dynamic parameterized problems and algorithms"):
  with members:
    - "fully dynamic maximal matching in constant update time"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "linear time kernelization for feedback vertex set"
    - "a linear time parameterized algorithm for directed feedback vertex set"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "dynamic graph connectivity with improved worst case update time and sublinear space"
    - "improved algorithms for decremental single source reachability on directed graphs"
    - "fast dynamic graph algorithms for parameterized problems"

Connected through hyperedge HE-6 (induced by source paper "enumeration and maximum number of minimal connected vertex covers in graphs"):
  with members:
    - "feedback vertex sets in tournaments"
    - "finding induced subgraphs via minimal triangulations"

Connected through hyperedge HE-7 (induced by source paper "preprocessing under uncertainty"):
  with members:
    - "network sparsification for steiner problems on planar and bounded genus graphs"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "finding small separators in linear time via treewidth reduction"
    - "computing minimum spanning trees with uncertainty"

Connected through hyperedge HE-8 (induced by source paper "approximation algorithms for connected maximum cut and related problems"):
  with members:
    - "a new perspective on vertex connectivity"
    - "analyzing the optimal neighborhood algorithms for budgeted and partial connected dominating set problems"
    - "submodular cost allocation problem and applications"

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)