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: "memcomputing np complete problems in polynomial time using polynomial resources and collective states"
  Abstract: Memcomputing is a novel non-Turing paradigm of computation that uses interacting memory cells (memprocessors for short) to store and process information on the same physical platform. It was recently proven mathematically that memcomputing machines have the same computational power of nondeterministic Turing machines. Therefore, they can solve NP-complete problems in polynomial time and, using the appropriate architecture, with resources that only grow polynomially with the input size. The reason for this computational power stems from properties inspired by the brain and shared by any universal memcomputing machine, in particular intrinsic parallelism and information overhead, namely, the capability of compressing information in the collective state of the memprocessor network. We show an experimental demonstration of an actual memcomputing architecture that solves the NP-complete version of the subset sum problem in only one step and is composed of a number of memprocessors that scales linearly with the size of the problem. We have fabricated this architecture using standard microelectronic technology so that it can be easily realized in any laboratory setting. Although the particular machine presented here is eventually limited by noise—and will thus require error-correcting codes to scale to an arbitrary number of memprocessors—it represents the first proof of concept of a machine capable of working with the collective state of interacting memory cells, unlike the present-day single-state machines built using the von Neumann architecture.

Connected through hyperedge HE-1 (induced by source paper "a scalable photonic computer solving the subset sum problem"):
  with members:
    - "universal memcomputing machines"
    - "a faster pseudopolynomial time algorithm for subset sum"
    - "the parallel approach"
    - "solving the subset sum problem with a light based device"

Connected through hyperedge HE-2 (induced by source paper "aircraft loading optimization memcomputing the 5th airbus problem"):
  with members:
    - "a quantum inspired classical algorithm for recommendation systems"
    - "accelerating deep learning with memcomputing"
    - "stress testing memcomputing on hard combinatorial optimization problems"
    - "instantons in self organizing logic gates"
    - "memcomputing integer linear programming"
    - "perspective memcomputing leveraging memory and physics to compute efficiently"
    - "polynomial time solution of prime factorization and np complete problems with digital memcomputing machines"
    - "universal memcomputing machines"

Connected through hyperedge HE-3 (induced by source paper "asymptotic behavior of memristive circuits"):
  with members:
    - "a tutorial on formulating and using qubo models"
    - "memristors for the curious outsiders"
    - "memory and information processing in neuromorphic systems"
    - "universal memcomputing machines"
    - "self organization and solution of shortest path optimization problems with memristive networks"

Connected through hyperedge HE-4 (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-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 with membrane memcapacitive systems"
    - "dynamic computing random access memory"
    - "the parallel approach"
    - "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"
    - "the parallel approach"

Connected through hyperedge HE-7 (induced by source paper "memcomputing numerical inversion with self organizing logic gates"):
  with members:
    - "universal memcomputing machines"
    - "deep learning in neural networks"
    - "the parallel approach"
    - "minimizing communication in linear algebra"

Connected through hyperedge HE-8 (induced by source paper "perspectives of using oscillators for computing and signal processing"):
  with members:
    - "a survey of neuromorphic computing and neural networks in hardware"
    - "the parallel approach"

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)