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: "faster exponential time algorithms in graphs of bounded average degree"
  Abstract: We first show that the Traveling Salesman Problem in an n-vertex graph with average degree bounded by d can be solved in O*(2^{(1-\eps_d)n}) time and exponential space for a constant \eps_d depending only on d, where the O*-notation suppresses factors polynomial in the input size. Thus, we generalize the recent results of Bjorklund et al. [TALG 2012] on graphs of bounded degree. #R##N#Then, we move to the problem of counting perfect matchings in a graph. We first present a simple algorithm for counting perfect matchings in an n-vertex graph in O*(2^{n/2}) time and polynomial space; our algorithm matches the complexity bounds of the algorithm of Bjorklund [SODA 2012], but relies on inclusion-exclusion principle instead of algebraic transformations. Building upon this result, we show that the number of perfect matchings in an n-vertex graph with average degree bounded by d can be computed in O*(2^{(1-\eps_{2d})n/2}) time and exponential space, where \eps_{2d} is the constant obtained by us for the Traveling Salesman Problem in graphs of average degree at most 2d. #R##N#Moreover we obtain a simple algorithm that counts the number of perfect matchings in an n-vertex bipartite graph of average degree at most d in O*(2^{(1-1/(3.55d))n/2}) time, improving and simplifying the recent result of Izumi and Wadayama [FOCS 2012].

Connected through hyperedge HE-1 (induced by source paper "a faster hafnian formula for complex matrices and its benchmarking on the titan supercomputer"):
  with members:
    - "the classical complexity of boson sampling"
    - "counting perfect matchings as fast as ryser"
    - "invitation to algorithmic uses of inclusion exclusion"

Connected through hyperedge HE-2 (induced by source paper "counting integral points in polytopes via numerical analysis of contour integration"):
  with members:
    - "counting perfect matchings as fast as ryser"

Connected through hyperedge HE-3 (induced by source paper "directed hamiltonicity and out branchings via generalized laplacians"):
  with members:
    - "on problems as hard as cnf sat"
    - "spotting trees with few leaves"
    - "fast algorithms for parameterized problems with relaxed disjointness constraints"
    - "mixing color coding related techniques"
    - "the parity of directed hamiltonian cycles"
    - "a new direction for counting perfect matchings"
    - "below all subsets for some permutational counting problems"
    - "fast hamiltonicity checking via bases of perfect matchings"

Connected through hyperedge HE-4 (induced by source paper "families with infants speeding up algorithms for np hard problems using fft"):
  with members:
    - "families with infants a general approach to solve hard partition problems"
    - "a new direction for counting perfect matchings"
    - "fast hamiltonicity checking via bases of perfect matchings"
    - "counting perfect matchings as fast as ryser"
    - "narrow sieves for parameterized paths and packings"
    - "determinant sums for undirected hamiltonicity"
    - "trimmed moebius inversion and graphs of bounded degree"

Connected through hyperedge HE-5 (induced by source paper "families with infants a general approach to solve hard partition problems"):
  with members:
    - "a new direction for counting perfect matchings"
    - "fast hamiltonicity checking via bases of perfect matchings"
    - "counting perfect matchings as fast as ryser"
    - "determinant sums for undirected hamiltonicity"
    - "trimmed moebius inversion and graphs of bounded degree"

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)