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: "are stable instances easy"
  Abstract: We introduce the notion of a stable instance for a discrete optimization problem, and argue that in many practical situations only sufficiently stable instances are of interest. The question then arises whether stable instances of NP--hard problems are easier to solve. In particular, whether there exist algorithms that solve correctly and in polynomial time all sufficiently stable instances of some NP--hard problem. The paper focuses on the Max--Cut problem, for which we show that this is indeed the case.

Connected through hyperedge HE-1 (induced by source paper "on the unreasonable effectiveness of the greedy algorithm greedy adapts to sharpness"):
  with members:
    - "guess free maximization of submodular and linear sums"
    - "stability and recovery for independence systems"
    - "constrained submodular maximization beyond 1 e"
    - "stability of influence maximization"
    - "deterministic algorithms for submodular maximization problems"
    - "computational feasibility of clustering under clusterability assumptions"
    - "lazier than lazy greedy"
    - "curvature and optimal algorithms for learning and minimizing submodular functions"

Connected through hyperedge HE-2 (induced by source paper "minimum enclosing ball revisited stability and sub linear time algorithms"):
  with members:
    - "beyond worst case analysis"
    - "varepsilon coresets for clustering with outliers in doubling metrics"
    - "coresets and sketches"
    - "locating a small cluster privately"
    - "k center clustering under perturbation resilience"
    - "optimization algorithms for faster computational geometry"
    - "approximation and streaming algorithms for projective clustering via random projections"
    - "clustering under perturbation resilience"

Connected through hyperedge HE-3 (induced by source paper "solving k 1 stable instances of k terminal cut with isolating cuts"):
  with members:
    - "bilu linial stable instances of max cut and minimum multiway cut"
    - "multiway cut pairwise realizable distributions and descending thresholds"
    - "rounding algorithms for a geometric embedding of minimum multiway cut"

Connected through hyperedge HE-4 (induced by source paper "beyond worst case analysis"):
  with members:
    - "being robust in high dimensions can be practical"
    - "implicit regularization in deep learning"
    - "a friendly smoothed analysis of the simplex method"
    - "how to escape saddle points efficiently"
    - "local max cut in smoothed polynomial time"
    - "a nearly tight sum of squares lower bound for the planted clique problem"
    - "understanding deep learning requires rethinking generalization"
    - "how robust are reconstruction thresholds for community detection"

Connected through hyperedge HE-5 (induced by source paper "on euclidean k means clustering with alpha center proximity"):
  with members:
    - "exact algorithms and lower bounds for stable instances of euclidean k means"
    - "approximation schemes for clustering with outliers"
    - "clustering stable instances of euclidean k means"
    - "better guarantees for k means and euclidean k median by primal dual algorithms"
    - "local search yields a ptas for k means in doubling metrics"
    - "local search yields approximation schemes for k means and k median in euclidean and minor free metrics"
    - "k center clustering under perturbation resilience"
    - "computational feasibility of clustering under clusterability assumptions"

Connected through hyperedge HE-6 (induced by source paper "an experimental study of algorithms for online bipartite matching"):
  with members:
    - "on conceptually simple algorithms for variants of online bipartite matching"
    - "on the power of advice and randomization for online bipartite matching"
    - "greedy online bipartite matching on random graphs"
    - "online stochastic matching beating 1 1 e"

Connected through hyperedge HE-7 (induced by source paper "a polynomial time algorithm for 2 2 k stable instances of the k terminal cut problem"):
  with members:
    - "bilu linial stable instances of max cut and minimum multiway cut"
    - "rounding algorithms for a geometric embedding of minimum multiway cut"

Connected through hyperedge HE-8 (induced by source paper "robust communication optimal distributed clustering algorithms"):
  with members:
    - "perturbation resilient clustering for k center and related problems via lp relaxations"
    - "distributed partial clustering"
    - "constant approximation for k median and k means with outliers via iterative rounding"
    - "communication optimal distributed clustering"
    - "approximation algorithms for clustering problems with lower bounds and outliers"
    - "better guarantees for k means and euclidean k median by primal dual algorithms"
    - "data driven resource allocation for distributed learning"
    - "k center clustering under perturbation resilience"

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.CC(Computational Complexity)