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: "symbiosis of search and heuristics for random 3 sat"
  Abstract: Delft University of Technology, Delft, The NetherlandsAbstract. When combined properly, search techniques can reveal the full poten-tial of sophisticated branching heuristics. We demonstrate this observation on thewell-known class of random 3-SAT formulae. First, a new branching heuristic ispresented, which generalizes existing work on this class. Much smaller searchtrees can be constructed by using this heuristic. Second, we introduce a variantof discrepancy search, called ALDS. Theoretical and practical evidence supportthat ALDS traverses the search tree in a near-optimal order when combined withthe new heuristic. Both techniques, search and heuristic, have been implementedin the look-ahead solvermarch. The SAT 2009 competition results show thatmarch is by far the strongest complete solver on random k-SAT formulae.

Connected through hyperedge HE-1 (induced by source paper "guiding high performance sat solvers with unsat core predictions"):
  with members:
    - "learning a sat solver from single bit supervision"
    - "learning to branch"
    - "gamepad a learning environment for theorem proving"
    - "robustfill neural program learning under noisy i o"
    - "ray a distributed framework for emerging ai applications"
    - "schur number five"
    - "deep network guided proof search"
    - "holstep a machine learning dataset for higher order logic theorem proving"

Connected through hyperedge HE-2 (induced by source paper "solving and verifying the boolean pythagorean triples problem via cube and conquer"):
  with members:
    - "satisfiability and computing van der waerden numbers"

Connected through hyperedge HE-3 (induced by source paper "concurrent cube and conquer"):
  with members:
    - "satzilla portfolio based algorithm selection for sat"

Connected through hyperedge HE-4 (induced by source paper "proteus a hierarchical portfolio of solvers and transformations"):
  with members:
    - "llama leveraging learning to automatically manage algorithms"
    - "algorithm selection for combinatorial search problems a survey"
    - "machine learning for constraint solver design a case study for the alldifferent constraint"
    - "xml representation of constraint networks format xcsp 2 1"
    - "restart strategy selection using machine learning techniques"
    - "satzilla portfolio based algorithm selection for sat"

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)