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: "the parallel approach"
  Abstract: A class of two-terminal passive circuit elements that can also act as memories could be the building blocks of a form of massively parallel computation known as memcomputing.

Connected through hyperedge HE-1 (induced by source paper "a scalable photonic computer solving the subset sum problem"):
  with members:
    - "universal memcomputing machines"
    - "memcomputing np complete problems in polynomial time using polynomial resources and collective states"
    - "a faster pseudopolynomial time algorithm for subset sum"
    - "solving the subset sum problem with a light based device"

Connected through hyperedge HE-2 (induced by source paper "transient dynamics of pulse driven memristors in the presence of a stable fixed point"):
  with members:
    - "a demonstration of implication logic based on volatile diffusive memristors"
    - "importance of the window function choice for the predictive modelling of memristors"
    - "training and operation of an integrated neuromorphic network based on metal oxide memristors"
    - "self organization and solution of shortest path optimization problems with memristive networks"

Connected through hyperedge HE-3 (induced by source paper "memristors for the curious outsiders"):
  with members:
    - "a neuromorphic systems approach to in memory computing with non ideal memristive devices from mitigation to exploitation"
    - "hierarchical temporal memory using memristor networks a survey"
    - "thermodynamic ram technology stack"
    - "perspective memcomputing leveraging memory and physics to compute efficiently"
    - "the case for rejecting the memristor as a fundamental circuit element"
    - "vertex coloring of graphs via phase dynamics of coupled oscillatory networks"
    - "polynomial time solution of prime factorization and np complete problems with digital memcomputing machines"
    - "temporal correlation detection using computational phase change memory"

Connected through hyperedge HE-4 (induced by source paper "accelerating deep learning with memcomputing"):
  with members:
    - "instantons in self organizing logic gates"
    - "weighted contrastive divergence"
    - "perspective memcomputing leveraging memory and physics to compute efficiently"
    - "memcomputing numerical inversion with self organizing logic gates"
    - "evidence of an exponential speed up in the solution of hard optimization problems"
    - "polynomial time solution of prime factorization and np complete problems with digital memcomputing machines"
    - "universal memcomputing machines"
    - "batch normalization accelerating deep network training by reducing internal covariate shift"

Connected through hyperedge HE-5 (induced by source paper "perspective memcomputing leveraging memory and physics to compute efficiently"):
  with members:
    - "instantons in self organizing logic gates"
    - "polynomial time solution of prime factorization and np complete problems with digital memcomputing machines"
    - "universal memcomputing machines"
    - "memcomputing np complete problems in polynomial time using polynomial resources and collective states"
    - "memcomputing with membrane memcapacitive systems"
    - "dynamic computing random access memory"
    - "self organization and solution of shortest path optimization problems with memristive networks"

Connected through hyperedge HE-6 (induced by source paper "stress testing memcomputing on hard combinatorial optimization problems"):
  with members:
    - "accelerating deep learning with memcomputing"
    - "perspective memcomputing leveraging memory and physics to compute efficiently"
    - "on the universality of memcomputing machines"
    - "evidence of an exponential speed up in the solution of hard optimization problems"
    - "batch normalization accelerating deep network training by reducing internal covariate shift"
    - "memcomputing np complete problems in polynomial time using polynomial resources and collective states"

Connected through hyperedge HE-7 (induced by source paper "in memory computing on a photonic platform"):
  with members:
    - "mixed precision in memory computing"
    - "superconducting optoelectronic circuits for neuromorphic computing"
    - "temporal correlation detection using computational phase change memory"
    - "mixed precision memcomputing"
    - "buddy ram improving the performance and efficiency of bulk bitwise operations using dram"
    - "universal memcomputing machines"

Connected through hyperedge HE-8 (induced by source paper "mixed precision in memory computing"):
  with members:
    - "temporal correlation detection using computational phase change memory"
    - "mixed precision training of deep neural networks using computational memory"
    - "universal memcomputing machines"
    - "changing computing paradigms towards power efficiency"

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.ET(Emerging Technologies)