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: "greedy facility location algorithms analyzed using dual fitting with factor revealing lp"
  Abstract: In this paper, we will formalize the method of dual fitting and the idea of factor-revealing LP. This combination is used to design and analyze two greedy algorithms for the metric uncapacitated facility location problem. Their approximation factors are 1.861 and 1.61, with running times of O(mlog m) and O(n^3), respectively, where n is the total number of vertices and m is the number of edges in the underlying complete bipartite graph between cities and facilities. The algorithms are used to improve recent results for several variants of the problem.

Connected through hyperedge HE-1 (induced by source paper "cache optimization models and algorithms"):
  with members:
    - "learning to cache with no regrets"
    - "introduction to online convex optimization"
    - "cabaret leveraging recommendation systems for mobile edge caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "competitive caching with machine learned advice"
    - "online convex optimization and no regret learning algorithms guarantees and applications"
    - "show me the cache optimizing cache friendly recommendations for sequential content access"
    - "a reinforcement learning approach to proactive caching in wireless networks"

Connected through hyperedge HE-2 (induced by source paper "flexible graph connectivity approximating network design problems between 1 and 2 connectivity"):
  with members:
    - "5 4 approximation of minimum 2 edge connected spanning subgraph"
    - "how to secure matchings against edge failures"
    - "improved approximation for tree augmentation saving by rewiring"
    - "on the tree augmentation problem"
    - "robust assignments via ear decompositions and randomized rounding"
    - "a simplified 1 5 approximation algorithm for augmenting edge connectivity of a graph from 1 to 2"
    - "analytical approach to parallel repetition"

Connected through hyperedge HE-3 (induced by source paper "concave connection cost facility location and the star inventory routing problem"):
  with members:
    - "inventory routing problem with facility location"
    - "on the factor revealing lp approach for facility location with penalties"
    - "approximation algorithms for inventory problems with submodular or routing costs"
    - "an optimal bifactor approximation algorithm for the metric uncapacitated facility location problem"

Connected through hyperedge HE-4 (induced by source paper "a constant approximation for colorful k center"):
  with members:
    - "on the partition set cover problem"
    - "approximation schemes for clustering with outliers"
    - "constant approximation for k median and k means with outliers via iterative rounding"
    - "matroid and knapsack center problems"

Connected through hyperedge HE-5 (induced by source paper "approximation algorithms for distributionally robust stochastic optimization with black box distributions"):
  with members:
    - "online allocation with traffic spikes mixing adversarial and stochastic models"
    - "making the most of your samples"
    - "robust and maxmin optimization under matroid and knapsack uncertainty sets"
    - "thresholded covering algorithms for robust and max min optimization"

Connected through hyperedge HE-6 (induced by source paper "inventory routing problem with facility location"):
  with members:
    - "approximation algorithms for inventory problems with submodular or routing costs"
    - "better approximation bounds for the joint replenishment problem"

Connected through hyperedge HE-7 (induced by source paper "on facility location with general lower bounds"):
  with members:
    - "improved approximation guarantees for lower bounded facility location"
    - "an optimal bifactor approximation algorithm for the metric uncapacitated facility location problem"

Connected through hyperedge HE-8 (induced by source paper "conditional markov chain search for the simple plant location problem improves upper bounds on twelve korkel ghosh instances"):
  with members:
    - "markov chain methods for the bipartite boolean quadratic programming problem"

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)