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 "flattening a hierarchical clustering through active learning"):
  Abstract: We investigate active learning by pairwise similarity over the leaves of trees originating from hierarchical clustering procedures. In the realizable setting, we provide a full characterization of the number of queries needed to achieve perfect reconstruction of the tree cut. In the non-realizable setting, we rely on known important-sampling procedures to obtain regret and query complexity bounds. Our algorithms come with theoretical guarantees on the statistical error and, more importantly, lend themselves to linear-time implementations in the relevant parameters of the problem. We discuss such implementations, prove running time guarantees for them, and present preliminary experiments on real-world datasets showing the compelling practical performance of our algorithms as compared to both passive learning and simple active learning baselines.

Includes members:
  Member "generalized binary search for split neighborly problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "evolving neural networks through a reverse encoding tree")
  Member "diameter based active learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adaptive region based active learning")
  Member "near optimal bayesian active learning with correlated and noisy tests":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning in confusion batch active learning with noisy oracle")
  Member "clustering with same cluster queries":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "explainable k means and k medians clustering")
  Member "local algorithms for interactive clustering":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "diameter based interactive structure discovery")
  Member "efficient active learning of halfspaces an aggressive approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exploring representativeness and informativeness for active learning")
  Member "agnostic active learning without constraints":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")
  Member "adaptive submodularity theory and applications in active learning and stochastic optimization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "comprehensive and efficient data labeling via adaptive model scheduling")

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.LG(Machine Learning)