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 "non intrusive energy disaggregation using non negative matrix factorization with sum to k constraint"):
  Abstract: Energy disaggregation or non-intrusive load monitoring addresses the issue of extracting device-level energy consumption information by monitoring the aggregated signal at one single measurement point without installing meters on each individual device. Energy disaggregation can be formulated as a source separation problem, where the aggregated signal is expressed as linear combination of basis vectors in a matrix factorization framework. In this paper, an approach based on  Sum-to-k constrained non-negative matrix factorization  (S2K-NMF) is proposed. By imposing the sum-to- k  constraint and the non-negative constraint, S2K-NMF is able to effectively extract perceptually meaningful sources from complex mixtures. The strength of the proposed algorithm is demonstrated through two sets of experiments: Energy disaggregation in a residential smart home; and heating, ventilating, and air conditioning components energy monitoring in an industrial building testbed maintained at the Oak Ridge National Laboratory. Extensive experimental results demonstrate the superior performance of S2K-NMF as compared to state-of-the-art decomposition-based disaggregation algorithms.

Includes members:
  Member "cloud based deep learning of big eeg data for epileptic seizure prediction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on deep learning based brain computer interface recent advances and new frontiers")
  Member "innovation pursuit a new approach to subspace clustering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "minimal sample subspace learning theory and algorithms")
  Member "feature encoding in band limited distributed surveillance systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "person re identification using visual attention")
  Member "does disaggregated electricity feedback reduce domestic electricity consumption a systematic review of the literature":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "active collaborative sensing for energy breakdown")
  Member "missing spectrum data recovery in cognitive radio networks using piecewise constant nonnegative matrix factorization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "primary user localization and online radio cartography via structured tensor decomposition")
  Member "sparse modeling for image and vision processing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "finding the sparsest vectors in a subspace theory algorithms and applications")
  Member "an empirical investigation of v i trajectory based load signatures for non intrusive load monitoring":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "neural network ensembles to real time identification of plug level appliance measurements")

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.CE(Computational Engineering, Finance, and Science)