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: "on the optimality of pseudo polynomial algorithms for integer programming"
  Abstract: In the classic Integer Programming (IP) problem, the objective is to decide whether, for a given $m \times n$ matrix $A$ and an $m$-vector $b=(b_1,\dots, b_m)$, there is a non-negative integer $n$-vector $x$ such that $Ax=b$. Solving (IP) is an important step in numerous algorithms and it is important to obtain an understanding of the precise complexity of this problem as a function of natural parameters of the input. #R##N#The classic pseudo-polynomial time algorithm of Papadimitriou [J. ACM 1981] for instances of (IP) with a constant number of constraints was only recently improved upon by Eisenbrand and Weismantel [SODA 2018] and Jansen and Rohwedder [ArXiv 2018]. We continue this line of work and show that under the Exponential Time Hypothesis (ETH), the algorithm of Jansen and Rohwedder is nearly optimal. We also show that when the matrix $A$ is assumed to be non-negative, a component of Papadimitriou's original algorithm is already nearly optimal under ETH. #R##N#This motivates us to pick up the line of research initiated by Cunningham and Geelen [IPCO 2007] who studied the complexity of solving (IP) with non-negative matrices in which the number of constraints may be unbounded, but the branch-width of the column-matroid corresponding to the constraint matrix is a constant. We prove a lower bound on the complexity of solving (IP) for such instances and obtain optimal results with respect to a closely related parameter, path-width. Specifically, we prove matching upper and lower bounds for (IP) when the path-width of the corresponding column-matroid is a constant.

Connected through hyperedge HE-1 (induced by source paper "a row invariant parameterized algorithm for integer programming"):
  with members:
    - "a parameterized strongly polynomial algorithm for block structured integer programs"
    - "faster algorithms for integer programs with block structure"
    - "the complexity landscape of decompositional parameters for ilp"
    - "solving integer linear programs with a small number of global variables and constraints"
    - "voting and bribing in single exponential time"

Connected through hyperedge HE-2 (induced by source paper "on integer programming discrepancy and convolution"):
  with members:
    - "on problems equivalent to min convolution"
    - "on integer programming and convolution"
    - "tight complexity lower bounds for integer linear programming with few constraints"
    - "capacitated dynamic programming faster knapsack and graph algorithms"
    - "proximity results and faster algorithms for integer programming using the steinitz lemma"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "closing the gap for makespan scheduling via sparsification techniques"
    - "clustered integer 3sum via additive combinatorics"

Connected through hyperedge HE-3 (induced by source paper "on integer programming and convolution"):
  with members:
    - "on problems equivalent to min convolution"
    - "proximity results and faster algorithms for integer programming using the steinitz lemma"
    - "closing the gap for makespan scheduling via sparsification techniques"
    - "a near linear pseudopolynomial time algorithm for subset sum"
    - "clustered integer 3sum via additive combinatorics"

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)