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: "dealing with range anxiety in mean estimation via statistical queries"
  Abstract: In the statistical query (SQ) model an algorithm has access to an SQ oracle for the input distribution $D$ over $X$ instead of i.i.d.~ samples from $D$. Given a query function $\phi:X \rightarrow [-1,1]$, the oracle returns an estimate of ${\bf E}_{{\bf x}\sim D}[\phi({\bf x})]$ within some tolerance $\tau$. In a variety of natural problems it is necessary to estimate expectations of functions whose standard deviation is much smaller than the range. In this note we describe a nearly optimal algorithm for estimation of such expectations via statistical queries. As applications, we give algorithms for high dimensional mean estimation in the SQ model and in the distributed setting where only a single bit is communicated from each sample.

Connected through hyperedge HE-1 (induced by source paper "locally private mean estimation z test and tight confidence intervals"):
  with members:
    - "test without trust optimal locally private distribution testing"
    - "locally private hypothesis testing"
    - "practical locally private heavy hitters"
    - "differentially private testing of identity and closeness of discrete distributions"
    - "finite sample differentially private confidence intervals"
    - "heavy hitters and the structure of local privacy"
    - "priv it private and sample efficient identity testing"
    - "differentially private ordinary least squares"

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.LG(Machine Learning)