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: "the number of minimum k cuts improving the karger stein bound"
  Abstract: Given an edge-weighted graph, how many minimum $k$-cuts can it have? This is a fundamental question in the intersection of algorithms, extremal combinatorics, and graph theory. It is particularly interesting in that the best known bounds are algorithmic: they stem from algorithms that compute the minimum $k$-cut. #R##N#In 1994, Karger and Stein obtained a randomized contraction algorithm that finds a minimum $k$-cut in $O(n^{(2-o(1))k})$ time. It can also enumerate all such $k$-cuts in the same running time, establishing a corresponding extremal bound of $O(n^{(2-o(1))k})$. Since then, the algorithmic side of the minimum $k$-cut problem has seen much progress, leading to a deterministic algorithm based on a tree packing result of Thorup, which enumerates all minimum $k$-cuts in the same asymptotic running time, and gives an alternate proof of the $O(n^{(2-o(1))k})$ bound. However, beating the Karger--Stein bound, even for computing a single minimum $k$-cut, has remained out of reach. #R##N#In this paper, we give an algorithm to enumerate all minimum $k$-cuts in $O(n^{(1.981+o(1))k})$ time, breaking the algorithmic and extremal barriers for enumerating minimum $k$-cuts. To obtain our result, we combine ideas from both the Karger--Stein and Thorup results, and draw a novel connection between minimum $k$-cut and extremal set theory. In particular, we give and use tighter bounds on the size of set systems with bounded dual VC-dimension, which may be of independent interest.

Connected through hyperedge HE-1 (induced by source paper "faster minimum k cut of a simple graph"):
  with members:
    - "lp relaxation and tree packing for minimum k cuts"
    - "faster exact and approximate algorithms for k cut"
    - "local flow partitioning for faster edge connectivity"
    - "if the current clique algorithms are optimal so is valiant s parser"
    - "powers of tensors and fast matrix multiplication"
    - "deterministic edge connectivity in near linear time"
    - "designing fpt algorithms for cut problems using randomized contractions"
    - "tight approximation ratio of a general greedy splitting algorithm for the minimum k way cut problem"

Connected through hyperedge HE-2 (induced by source paper "the karger stein algorithm is optimal for k cut"):
  with members:
    - "faster minimum k cut of a simple graph"
    - "lp relaxation and tree packing for minimum k cuts"
    - "faster exact and approximate algorithms for k cut"

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)