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: "lp branching algorithms based on biased graphs"
  Abstract: We give a combinatorial condition for the existence of efficient, LP-based FPT algorithms for a broad class of graph-theoretical optimisation problems. Our condition is based on the notion of biased graphs known from matroid theory. Specifically, we show that given a biased graph $\Psi=(G,\mathcal{B})$, where $\mathcal{B}$ is a class of balanced cycles in $G$, the problem of finding a set $X$ of at most $k$ vertices in $G$ which intersects every unbalanced cycle in $G$ admits an FPT algorithm using an LP-branching approach, similar to those previously seen for VCSP problems (Wahlstr\"om, SODA 2014). Our algorithm has two parts. First we define a \emph{local problem}, where we are additionally given a root vertex $v_0 \in V$ and asked only to delete vertices $X$ (excluding $v_0$) so that the connected component of $v_0$ in $G-X$ contains no unbalanced cycle. We show that this local problem admits a persistent, half-integral LP-relaxation with a polynomial-time solvable separation oracle, and can therefore be solved in FPT time via LP-branching, assuming only oracle membership queries for the class of balanced cycles in $G$. We then show that solutions to this local problem can be used to tile the graph, producing an optimal solution to the original, global problem as well. This framework captures many of the problems previously solved via the VCSP approach to LP-branching, as well as new generalisations, such as Group Feedback Vertex Set for infinite groups (e.g., for graphs whose edges are labelled by matrices). A major advantage compared to previous work is that it is immediate to check the applicability of the result for a given problem, whereas testing applicability of the VCSP approach for a specific VCSP requires determining the existence of an embedding language with certain algebraically defined properties, which is not known to be decidable in general.

Connected through hyperedge HE-1 (induced by source paper "on quasipolynomial multicut mimicking networks and kernelization of multiway cut problems"):
  with members:
    - "randomized contractions meet lean decompositions"
    - "vertex sparsifiers new results from old techniques"
    - "deterministic truncation of linear matroids"
    - "on vertex sparsifiers with steiner nodes"
    - "mimicking networks and succinct representations of terminal cuts"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "compression via matroids a randomized polynomial kernel for odd cycle transversal"

Connected through hyperedge HE-2 (induced by source paper "evaluating graph bipartization methods for applications in quantum computing"):
  with members:
    - "0 1 all csps half integral a path packing and linear time fpt algorithms"
    - "a study of complex deep learning networks on high performance neuromorphic and quantum computers"
    - "linear time fpt algorithms via network flow"
    - "faster parameterized algorithms using linear programming"
    - "compression via matroids a randomized polynomial kernel for odd cycle transversal"

Connected through hyperedge HE-3 (induced by source paper "0 1 all csps half integral a path packing and linear time fpt algorithms"):
  with members:
    - "parameterized algorithms for zero extension and metric labelling problems"
    - "a linear time parameterized algorithm for node unique label cover"
    - "linear time kernelization for feedback vertex set"
    - "a linear time parameterized algorithm for directed feedback vertex set"
    - "a dual descent algorithm for node capacitated multiflow problems and its applications"
    - "linear time parameterized algorithms via skew symmetric multicuts"
    - "linear time fpt algorithms via network flow"
    - "faster parameterized algorithms using linear programming"

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)