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 "the art of trellis decoding is fixed parameter tractable"):
  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 trellis-width (or minimum trellis state-complexity) of a linear code in coding theory and computing the path-width of an    $\mathbb F$   -represented matroid in matroid theory. 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. 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    $k$   . An algorithm by Hliněný (2006) can detect a minor in an input    $\mathbb F$   -represented matroid of bounded branch-width. However, this indirect approach would not produce an actual path-decomposition. Our algorithm is the first one to construct such a path-decomposition and does not depend on the finiteness of forbidden minors.

Includes members:
  Member "an fpt algorithm and a polynomial kernel for linear rankwidth 1 vertex deletion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "measuring what matters a hybrid approach to dynamic programming with treewidth")
  Member "constructive algorithm for path width of matroids":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an fpt 2 approximation for tree cut decomposition")
  Member "myhill nerode methods for hypergraphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")
  Member "fast matrix rank algorithms and applications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "elimination based certificates for triangular equivalence and rank profiles")
  Member "matroid pathwidth and code trellis complexity":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "comparing linear width parameters for directed graphs")

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)