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 "lattice sparsification and the approximate closest vector problem"):
  Abstract: We give a deterministic algorithm for solving the (1+eps)-approximate Closest Vector Problem (CVP) on any n dimensional lattice and any norm in 2^{O(n)}(1+1/eps)^n time and 2^n poly(n) space. Our algorithm builds on the lattice point enumeration techniques of Micciancio and Voulgaris (STOC 2010) and Dadush, Peikert and Vempala (FOCS 2011), and gives an elegant, deterministic alternative to the "AKS Sieve" based algorithms for (1+eps)-CVP (Ajtai, Kumar, and Sivakumar; STOC 2001 and CCC 2002). Furthermore, assuming the existence of a poly(n)-space and 2^{O(n)} time algorithm for exact CVP in the l_2 norm, the space complexity of our algorithm can be reduced to polynomial. #R##N#Our main technical contribution is a method for "sparsifying" any input lattice while approximately maintaining its metric structure. To this end, we employ the idea of random sublattice restrictions, which was first employed by Khot (FOCS 2003) for the purpose of proving hardness for Shortest Vector Problem (SVP) under l_p norms.

Includes members:
  Member "tensor based hardness of the shortest vector problem to within almost polynomial factors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hardness of bounded distance decoding on lattices in ell_p norms")
  Member "a o 1 eps 2 n time sieving algorithm for approximate integer programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "covering convex bodies and the closest vector problem")
  Member "covering cubes and the closest vector problem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "faster provable sieving algorithms for the shortest vector problem and the closest vector problem on lattices in 120001 p norm")
  Member "enumerative lattice algorithms in any norm via m ellipsoid coverings":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "faster provable sieving algorithms for the shortest vector problem and the closest vector problem on lattices in 120001 p norm")
  Member "improved analysis of kannan s shortest lattice vector algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improved provable algorithms for the shortest vector problem via bounded distance decoding")

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)