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 "evaluating and tuning n fold integer programming"):
  Abstract: In recent years, algorithmic breakthroughs in stringology, computational social choice, scheduling, etc., were achieved by applying the theory of so-called $n$-fold integer programming. An $n$-fold integer program (IP) has a highly uniform block structured constraint matrix. Hemmecke, Onn, and Romanchuk [Math. Programming, 2013] showed an algorithm with runtime $a^{O(rst + r^2s)} n^3$, where $a$ is the largest coefficient, $r,s$, and $t$ are dimensions of blocks of the constraint matrix and $n$ is the total dimension of the IP; thus, an algorithm efficient if the blocks are of small size and with small coefficients. The algorithm works by iteratively improving a feasible solution with augmenting steps, and $n$-fold IPs have the special property that augmenting steps are guaranteed to exist in a not-too-large neighborhood. #R##N#We have implemented the algorithm and learned the following along the way. The original algorithm is practically unusable, but we discover a series of improvements which make its evaluation possible. Crucially, we observe that a certain constant in the algorithm can be treated as a tuning parameter, which yields an efficient heuristic (essentially searching in a smaller-than-guaranteed neighborhood). Furthermore, the algorithm uses an overly expensive strategy to find a "best" step, while finding only an "approximatelly best" step is much cheaper, yet sufficient for quick convergence. Using this insight, we improve the asymptotic dependence on $n$ from $n^3$ to $n^2 \log n$. #R##N#We show that decreasing the tuning parameter initially leads to an increased number of iterations needed for convergence and eventually to getting stuck in local optima, as expected. However, surprisingly small values of the parameter already exhibit good behavior. Second, our new strategy for finding "approximatelly best" steps wildly outperforms the original construction.

Includes members:
  Member "a parameterized strongly polynomial algorithm for block structured integer programs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "n fold integer programming via lp rounding")
  Member "faster algorithms for integer programs with block structure":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "n fold integer programming via lp rounding")
  Member "empowering the configuration ip new ptas results for scheduling with setups times":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "n fold integer programming via lp rounding")
  Member "near linear time algorithm for n fold ilps via color coding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "n fold integer programming via lp rounding")
  Member "scheduling meets n fold integer programming":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "n fold integer programming via lp rounding")
  Member "combinatorial n fold integer programming and applications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "n fold integer programming via lp rounding")
  Member "voting and bribing in single exponential time":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "n fold integer programming via lp rounding")

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)