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: "improved approximation algorithms for k submodular function maximization"
  Abstract: This paper presents a polynomial-time $1/2$-approximation algorithm for maximizing nonnegative $k$-submodular functions. This improves upon the previous $\max\{1/3, 1/(1+a)\}$-approximation by Ward and \v{Z}ivn\'y~(SODA'14), where $a=\max\{1, \sqrt{(k-1)/4}\}$. We also show that for monotone $k$-submodular functions there is a polynomial-time $k/(2k-1)$-approximation algorithm while for any $\varepsilon>0$ a $((k+1)/2k+\varepsilon)$-approximation algorithm for maximizing monotone $k$-submodular functions would require exponentially many queries. In particular, our hardness result implies that our algorithms are asymptotically tight. #R##N#We also extend the approach to provide constant factor approximation algorithms for maximizing skew-bisubmodular functions, which were recently introduced as generalizations of bisubmodular functions.

Connected through hyperedge HE-1 (induced by source paper "improved randomized algorithm for k submodular function maximization"):
  with members:
    - "maximizing k submodular functions and beyond"
    - "deterministic algorithms for submodular maximization problems"
    - "towards minimizing k submodular functions"

Connected through hyperedge HE-2 (induced by source paper "no regret algorithms for online k submodular maximization"):
  with members:
    - "introduction to online convex optimization"
    - "an optimal algorithm for online unconstrained submodular maximization"
    - "derandomization for k submodular maximization"
    - "maximizing k submodular functions and beyond"
    - "on maximizing a monotone k submodular function subject to a matroid constraint"
    - "online submodular maximization under a matroid constraint with application to learning assignments"
    - "towards minimizing k submodular functions"

Connected through hyperedge HE-3 (induced by source paper "on maximizing a monotone k submodular function subject to a matroid constraint"):
  with members:
    - "maximizing k submodular functions and beyond"
    - "towards minimizing k submodular functions"
    - "potts model parametric maxflow and k submodular functions"
    - "a tight combinatorial algorithm for submodular maximization subject to a matroid constraint"
    - "adaptive submodular optimization under matroid constraints"

Connected through hyperedge HE-4 (induced by source paper "derandomization for k submodular maximization"):
  with members:
    - "maximizing k submodular functions and beyond"
    - "deterministic algorithms for submodular maximization problems"
    - "towards minimizing k submodular functions"
    - "potts model parametric maxflow and k submodular functions"

Connected through hyperedge HE-5 (induced by source paper "maximizing monotone submodular functions over the integer lattice"):
  with members:
    - "deterministic algorithms for submodular maximization problems"
    - "submodular function maximization on the bounded integer lattice"
    - "how to influence people with partial incentives"
    - "online submodular welfare maximization greedy is optimal"

Connected through hyperedge HE-6 (induced by source paper "maximizing symmetric submodular functions"):
  with members:
    - "constrained submodular maximization via a non symmetric technique"
    - "constrained submodular maximization beyond 1 e"
    - "deterministic algorithms for submodular maximization problems"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"
    - "on the approximation of submodular functions"
    - "symmetry and approximability of submodular maximization problems"
    - "approximation algorithms for submodular multiway partition"
    - "submodular function maximization via the multilinear relaxation and contention resolution schemes"

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)