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 kadison singer problem for strongly rayleigh measures and applications to asymmetric tsp"
  Abstract: Marcus, Spielman, and Srivastava in their seminal work \cite{MSS13} resolved the Kadison-Singer conjecture by proving that for any set of finitely supported independently distributed random vectors $v_1,\dots, v_n$ which have "small" expected squared norm and are in isotropic position (in expectation), there is a positive probability that the sum $\sum v_i v_i^\intercal$ has small spectral norm. Their proof crucially employs real stability of polynomials which is the natural generalization of real-rootedness to multivariate polynomials. #R##N#Strongly Rayleigh distributions are families of probability distributions whose generating polynomials are real stable \cite{BBL09}. As independent distributions are just special cases of strongly Rayleigh measures, it is a natural question to see if the main theorem of \cite{MSS13} can be extended to families of vectors assigned to the elements of a strongly Rayleigh distribution. #R##N#In this paper we answer this question affirmatively; we show that for any homogeneous strongly Rayleigh distribution where the marginal probabilities are upper bounded by $\epsilon_1$ and any isotropic set of vectors assigned to the underlying elements whose norms are at most $\sqrt{\epsilon_2}$, there is a set in the support of the distribution such that the spectral norm of the sum of the natural quadratic forms of the vectors assigned to the elements of the set is at most $O(\epsilon_1+\epsilon_2)$. We employ our theorem to provide a sufficient condition for the existence of spectrally thin trees. This, together with a recent work of the authors \cite{AO14}, provides an improved upper bound on the integrality gap of the natural LP relaxation of the Asymmetric Traveling Salesman Problem.

Connected through hyperedge HE-1 (induced by source paper "the ising partition function zeros and deterministic approximation"):
  with members:
    - "a generalization of permanent inequalities and applications in counting and optimization"
    - "convergence of mcmc and loopy bp in the tree uniqueness region for the hard core model"
    - "real stable polynomials and matroids optimization and counting"
    - "random cluster dynamics for the ising model is rapidly mixing"
    - "uniqueness spatial mixing and approximation for ferromagnetic 2 spin systems"
    - "fptas for hardcore and ising models on hypergraphs"
    - "counting hypergraph matchings up to uniqueness threshold"
    - "the complexity of approximately counting in 2 spin systems on k uniform bounded degree hypergraphs"

Connected through hyperedge HE-2 (induced by source paper "a generalization of permanent inequalities and applications in counting and optimization"):
  with members:
    - "real stable polynomials and matroids optimization and counting"
    - "effective resistance reducing flows spectrally thin trees and asymmetric tsp"

Connected through hyperedge HE-3 (induced by source paper "fast sampling for strongly rayleigh measures with application to determinantal point processes"):
  with members:
    - "learning with submodular functions a convex optimization perspective"

Connected through hyperedge HE-4 (induced by source paper "approximation algorithms for finding maximum induced expanders"):
  with members:
    - "effective resistance reducing flows spectrally thin trees and asymmetric tsp"
    - "partitioning into expanders"
    - "approximating the expansion profile and almost optimal local graph clustering"
    - "min max graph partitioning and small set expansion"
    - "a local clustering algorithm for massive graphs and its application to nearly linear time graph partitioning"
    - "finding sparse cuts locally using evolving sets"

Connected through hyperedge HE-5 (induced by source paper "approximating atsp by relaxing connectivity"):
  with members:
    - "effective resistance reducing flows spectrally thin trees and asymmetric tsp"
    - "new inapproximability bounds for tsp"
    - "approximating graphic tsp by matchings"
    - "13 9 approximation for graphic tsp"
    - "the asymmetric traveling salesman problem on graphs with bounded genus"

Connected through hyperedge HE-6 (induced by source paper "effective resistance reducing flows spectrally thin trees and asymmetric tsp"):
  with members:
    - "approximating atsp by relaxing connectivity"
    - "a near optimal approximation algorithm for asymmetric tsp on embedded graphs"
    - "pipage rounding pessimistic estimators and matrix concentration"
    - "a randomized rounding algorithm for the asymmetric traveling salesman problem"
    - "the asymmetric traveling salesman problem on graphs with bounded genus"
    - "twice ramanujan sparsifiers"
    - "graph sparsification by effective resistances"
    - "nearly linear time algorithms for graph partitioning graph sparsification and solving linear systems"

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)