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: "bilu linial stable instances of max cut and minimum multiway cut"
  Abstract: We investigate the notion of stability proposed by Bilu and Linial. We obtain an exact polynomial-time algorithm for $\gamma$-stable Max Cut instances with $\gamma \geq c\sqrt{\log n}\log\log n$ for some absolute constant $c > 0$. Our algorithm is robust: it never returns an incorrect answer; if the instance is $\gamma$-stable, it finds the maximum cut, otherwise, it either finds the maximum cut or certifies that the instance is not $\gamma$-stable. We prove that there is no robust polynomial-time algorithm for $\gamma$-stable instances of Max Cut when $\gamma < \alpha_{SC}(n/2)$, where $\alpha_{SC}$ is the best approximation factor for Sparsest Cut with non-uniform demands. #R##N#Our algorithm is based on semidefinite programming. We show that the standard SDP relaxation for Max Cut (with $\ell_2^2$ triangle inequalities) is integral if $\gamma \geq D_{\ell_2^2\to \ell_1}(n)$, where $D_{\ell_2^2\to \ell_1}(n)$ is the least distortion with which every $n$ point metric space of negative type embeds into $\ell_1$. On the negative side, we show that the SDP relaxation is not integral when $\gamma < D_{\ell_2^2\to \ell_1}(n/2)$. Moreover, there is no tractable convex relaxation for $\gamma$-stable instances of Max Cut when $\gamma < \alpha_{SC}(n/2)$. That suggests that solving $\gamma$-stable instances with $\gamma =o(\sqrt{\log n})$ might be difficult or impossible. #R##N#Our results significantly improve previously known results. The best previously known algorithm for $\gamma$-stable instances of Max Cut required that $\gamma \geq c\sqrt{n}$ (for some $c > 0$) [Bilu, Daniely, Linial, and Saks]. No hardness results were known for the problem. Additionally, we present an algorithm for 4-stable instances of Minimum Multiway Cut. We also study a relaxed notion of weak stability.

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

Connected through hyperedge HE-2 (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-3 (induced by source paper "bilu linial stability certified algorithms and the independent set problem"):
  with members:
    - "on euclidean k means clustering with alpha center proximity"
    - "exact algorithms and lower bounds for stable instances of euclidean k means"
    - "perturbation resilient clustering for k center and related problems via lp relaxations"
    - "stability and recovery for independence systems"
    - "lp based robust algorithms for noisy minor free and bounded treewidth graphs"
    - "k center clustering under perturbation resilience"
    - "on the lov asz theta function for independent sets in sparse graphs"
    - "sum of squares lower bounds for planted clique"

Connected through hyperedge HE-4 (induced by source paper "exact algorithms and lower bounds for stable instances of euclidean k means"):
  with members:
    - "clustering stable instances of euclidean k means"
    - "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"
    - "on the practically interesting instances of maxcut"

Connected through hyperedge HE-5 (induced by source paper "a polynomial time algorithm for 2 2 k stable instances of the k terminal cut problem"):
  with members:
    - "are stable instances easy"
    - "rounding algorithms for a geometric embedding of minimum multiway cut"

Connected through hyperedge HE-6 (induced by source paper "stability and recovery for independence systems"):
  with members:
    - "k center clustering under perturbation resilience"
    - "computational feasibility of clustering under clusterability assumptions"
    - "the unreasonable success of local search geometric optimization"
    - "improved approximation for 3 dimensional matching via bounded pathwidth local search"
    - "large neighborhood local search for the maximum set packing problem"
    - "clustering is difficult only when it does not matter"
    - "on the practically interesting instances of maxcut"
    - "nash equilibria in perturbation resilient games"

Connected through hyperedge HE-7 (induced by source paper "approximate hierarchical clustering via sparsest cut and spreading metrics"):
  with members:
    - "a cost function for similarity based hierarchical clustering"
    - "robust hierarchical clustering"
    - "reductions between expansion problems"

Connected through hyperedge HE-8 (induced by source paper "k center clustering under perturbation resilience"):
  with members:
    - "improved and simplified inapproximability for k means"
    - "a bi criteria approximation algorithm for k means"
    - "an improved approximation for k median and positive correlation in budgeted optimization"
    - "decompositions of triangle dense graphs"
    - "on the practically interesting instances of maxcut"
    - "improved spectral norm bounds for clustering"
    - "beyond worst case analysis in private singular vector computation"
    - "learning topic models going beyond svd"

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)