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: "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.

Connected through hyperedge HE-1 (induced by source paper "new bounds on augmenting steps of block structured integer programs"):
  with members:
    - "a parameterized strongly polynomial algorithm for block structured integer programs"
    - "faster algorithms for integer programs with block structure"
    - "empowering the configuration ip new ptas results for scheduling with setups times"
    - "on integer programming and convolution"
    - "scheduling meets n fold integer programming"
    - "the complexity landscape of decompositional parameters for ilp"
    - "combinatorial n fold integer programming and applications"
    - "proximity results and faster algorithms for integer programming using the steinitz lemma"

Connected through hyperedge HE-2 (induced by source paper "near linear time algorithm for n fold ilps via color coding"):
  with members:
    - "a parameterized strongly polynomial algorithm for block structured integer programs"
    - "faster algorithms for integer programs with block structure"
    - "combinatorial n fold integer programming and applications"
    - "proximity results and faster algorithms for integer programming using the steinitz lemma"

Connected through hyperedge HE-3 (induced by source paper "mixed integer programming with convex concave constraints fixed parameter tractability and applications to multicovering and voting"):
  with members:
    - "a parameterized strongly polynomial algorithm for block structured integer programs"
    - "faster algorithms for integer programs with block structure"
    - "fair knapsack"
    - "scheduling meets n fold integer programming"
    - "combinatorial n fold integer programming and applications"
    - "integer programming in parameterized complexity three miniatures"
    - "solving integer linear programs with a small number of global variables and constraints"
    - "voting and bribing in single exponential time"

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)