human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "constant factor approximation for balanced cut in the pie model"):
  Abstract: We propose and study a new semi-random semi-adversarial model for Balanced Cut, a planted model with permutation-invariant random edges (PIE). Our model is much more general than planted models considered previously. Consider a set of vertices V partitioned into two clusters $L$ and $R$ of equal size. Let $G$ be an arbitrary graph on $V$ with no edges between $L$ and $R$. Let $E_{random}$ be a set of edges sampled from an arbitrary permutation-invariant distribution (a distribution that is invariant under permutation of vertices in $L$ and in $R$). Then we say that $G + E_{random}$ is a graph with permutation-invariant random edges. #R##N#We present an approximation algorithm for the Balanced Cut problem that finds a balanced cut of cost $O(|E_{random}|) + n \text{polylog}(n)$ in this model. In the regime when $|E_{random}| = \Omega(n \text{polylog}(n))$, this is a constant factor approximation with respect to the cost of the planted cut.

Includes members:
  Member "bilu linial stable instances of max cut and minimum multiway cut":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "solving k 1 stable instances of k terminal cut with isolating cuts")
  Member "on the practically interesting instances of maxcut":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bilu linial stability certified algorithms and the independent set problem")
  Member "clustering partially observed graphs via convex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "matrix completion with prior subspace information via maximizing correlation")
  Member "how to play unique games against a semi random adversary":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards learning sparsely used dictionaries with arbitrary supports")
  Member "center based clustering under perturbation stability":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "analysis of ward s method")
  Member "reductions between expansion problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "bisect and conquer hierarchical clustering via max uncut bisection")
  Member "are stable instances easy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the unreasonable effectiveness of the greedy algorithm greedy adapts to sharpness")

Question: Please tell me which class the source paper 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)