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: "exploiting hidden structure in selecting dimensions that distinguish vectors"
  Abstract: The NP-hard Distinct Vectors problem asks to delete as many columns as possible from a matrix such that all rows in the resulting matrix are still pairwise distinct. Our main result is that, for binary matrices, there is a complexity dichotomy for Distinct Vectors based on the maximum (H) and the minimum (h) pairwise Hamming distance between matrix rows: Distinct Vectors can be solved in polynomial time if H ? 2 ? h / 2 ? + 1 , and is NP-complete otherwise. Moreover, we explore connections of Distinct Vectors to hitting sets, thereby providing several fixed-parameter tractability and intractability results also for general matrices. Binary matrices solvable for small range of Hamming distances, NP-hard otherwise.Sunflowers as combinatorial tool for structural matrix analysis.FPT and W-hardness for general matrices.

Connected through hyperedge HE-1 (induced by source paper "optimal size problem kernels for d hitting set in linear time and space"):
  with members:
    - "understanding the effectiveness of data reduction in public transportation networks"
    - "on approximate data reduction for the rural postman problem theory and experiments"
    - "computing hitting set kernels by ac 0 circuits"
    - "efficiently enumerating hitting sets of hypergraphs arising in data profiling"
    - "a shortcut to sun flowers kernels in logarithmic space or linear time"
    - "towards optimal and expressive kernelization for d hitting set"

Connected through hyperedge HE-2 (induced by source paper "complexity of combinatorial matrix completion with diameter constraints"):
  with members:
    - "on clustering incomplete data"
    - "multivariate fine grained complexity of longest common subsequence"

Connected through hyperedge HE-3 (induced by source paper "efficiently enumerating hitting sets of hypergraphs arising in data profiling"):
  with members:
    - "the minimal hitting set generation problem algorithms and computation"
    - "randomised enumeration of small witnesses using a decision oracle"
    - "efficient enumeration of solutions produced by closure operations"
    - "a polynomial delay algorithm for enumerating minimal dominating sets in chordal graphs"
    - "paradigms for parameterized enumeration"
    - "efficient algorithms for dualizing large scale hypergraphs"
    - "new results on monotone dualization and generating hypergraph transversals"
    - "incremental recompilation of knowledge"

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.DM(Discrete Mathematics)