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: "dig enabling out of band scalable high resolution monitoring for data center analytics automation and control extended"
  Abstract: Data centers are increasing in size and complexity, and we need scalable approaches to support their automated analysis and control. Performance counters and power consumption are their key "vital signs". State-of-the-Art (SoA) monitoring systems provide built-in tools to collect performance measurements, and custom solutions to get insight on their power consumption. However, with the increase in measurement resolution (in time and space) and the ensuing huge amount of measurement data to handle, new challenges arise, such as bottlenecks on the network bandwidth, storage and software overhead on the monitoring units. To face these challenges we propose a novel monitoring platform for data centers, which enables real-time high-resolution profiling (i.e., all available performance counters and the entire signal bandwidth of the power consumption at the plug - sampling up to 20us - with an error below 1%) and analytics, both at the edge (node-level analysis) and on a centralized unit (cluster-level analysis). The monitoring infrastructure is completely out-of-band, scalable, technology agnostic and low cost, and it is already installed in a SoA high-performance compute cluster (i.e., D.A.V.I.D.E. - 18th in Green500 November 2017).

Connected through hyperedge HE-1 (induced by source paper "online anomaly detection in hpc systems"):
  with members:
    - "adam a method for stochastic optimization"
    - "what regularized auto encoders learn from the data generating distribution"

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.DC(Distributed, Parallel, and Cluster Computing)