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: "constructive algorithm for path width of matroids"
  Abstract: Given $n$ subspaces of a finite-dimensional vector space over a fixed finite field $\mathbb F$, we wish to find a linear layout $V_1,V_2,\ldots,V_n$ of the subspaces such that $\dim(V_1+V_2+\cdots+V_i)\cap(V_{i+1}+\cdots+V_n)\le k$ for all $i$; such a linear layout is said to have width at most $k$. When restricted to $1$-dimensional subspaces, this problem is equivalent to computing the path-width of an $\mathbb F$-represented matroid in matroid theory and computing the trellis-width (or minimum trellis state-complexity) of a linear code in coding theory. #R##N#We present a fixed-parameter tractable algorithm to construct a linear layout of width at most $k$, if it exists, for input subspaces of a finite-dimensional vector space over $\mathbb F$. As corollaries, we obtain a fixed-parameter tractable algorithm to produce a path-decomposition of width at most $k$ for an input $\mathbb F$-represented matroid of path-width at most $k$, and a fixed-parameter tractable algorithm to find a linear rank-decomposition of width at most $k$ for an input graph of linear rank-width at most $k$. In both corollaries, no such algorithms were known previously. Our approach is based on dynamic programming combined with the idea developed by Bodlaender and Kloks (1996) for their work on path-width and tree-width of graphs. #R##N#It was previously known that a fixed-parameter tractable algorithm exists for the decision version of the problem for matroid path-width; a theorem by Geelen, Gerards, and Whittle (2002) implies that for each fixed finite field $\mathbb F$, there are finitely many forbidden $\mathbb F$-representable minors for the class of matroids of path-width at most $k$. However, this indirect approach would not produce an actual path-decomposition even if the complete list of forbidden minors were known. Our algorithm is the first one to construct such a path-decomposition.

Connected through hyperedge HE-1 (induced by source paper "an fpt 2 approximation for tree cut decomposition"):
  with members:
    - "bidimensionality and eptas"
    - "finding topological subgraphs is fixed parameter tractable"

Connected through hyperedge HE-2 (induced by source paper "the art of trellis decoding is fixed parameter tractable"):
  with members:
    - "an fpt algorithm and a polynomial kernel for linear rankwidth 1 vertex deletion"
    - "myhill nerode methods for hypergraphs"
    - "fast matrix rank algorithms and applications"
    - "matroid pathwidth and code trellis complexity"

Connected through hyperedge HE-3 (induced by source paper "optimizing tree decompositions in mso"):
  with members:
    - "cutwidth obstructions and algorithmic aspects"
    - "computing tree depth faster than 2 n"

Connected through hyperedge HE-4 (induced by source paper "finding branch decompositions of matroids hypergraphs and more"):
  with members:
    - "the rank width of edge coloured graphs"

Connected through hyperedge HE-5 (induced by source paper "a simpler self reduction algorithm for matroid path width"):
  with members:
    - "matroid pathwidth and code trellis complexity"

Connected through hyperedge HE-6 (induced by source paper "an fpt algorithm and a polynomial kernel for linear rankwidth 1 vertex deletion"):
  with members:
    - "further kernelization of proper interval vertex deletion new observations and refined analysis"
    - "a single exponential fixed parameter algorithm for distance hereditary vertex deletion"
    - "unit interval editing is fixed parameter tractable"
    - "a note on graphs of linear rank width 1"
    - "interval deletion is fixed parameter tractable"
    - "a polynomial kernel for proper interval vertex deletion"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "a quartic kernel for pathwidth one vertex deletion"

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)