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 "stress testing memcomputing on hard combinatorial optimization problems"):
  Abstract: Memcomputing is a novel paradigm of computation that utilizes dynamical elements with memory to both store and process information on the same physical location. Its building blocks can be fabricated in hardware with standard electronic circuits, thus offering a path to its practical realization. In addition, since memcomputing is based on non-quantum elements, the equations of motion describing these machines can be simulated efficiently on standard computers. In fact, it was recently realized that memcomputing, and in particular its digital (hence scalable) version, when simulated on a classical machine provides a significant speed-up over state-of-the-art algorithms on a variety of non-convex problems. Here, we stress-test the capabilities of this approach on finding approximate solutions to hard combinatorial optimization problems. These fall into a class which is known to require exponentially growing resources in the worst cases, even to generate approximations. We recently showed that in a region where state of the art algorithms demonstrate this exponential growth, simulations of digital memcomputing machines performed using the Falcon$^\copyright$ simulator of MemComputing, Inc. only require time and memory resources that scale linearly. These results are extended in a stress-test up to $64\times10^6$ variables (corresponding to about 1 billion literals), namely the largest case that we could fit on a single node with 128 GB of DRAM. Since memcomputing can be applied to a wide variety of optimization problems, this stress test shows the considerable advantage of non-combinatorial, physics-inspired approaches over standard combinatorial ones.

Includes members:
  Member "accelerating deep learning with memcomputing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "aircraft loading optimization memcomputing the 5th airbus problem")
  Member "perspective memcomputing leveraging memory and physics to compute efficiently":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "p bits for probabilistic spin logic")
  Member "on the universality of memcomputing machines":
    also connected through other hyperedges:
      (none)
  Member "evidence of an exponential speed up in the solution of hard optimization problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "accelerating deep learning with memcomputing")
  Member "batch normalization accelerating deep network training by reducing internal covariate shift":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "discrimination aware network pruning for deep model compression")
  Member "memcomputing np complete problems in polynomial time using polynomial resources and collective states":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a scalable photonic computer solving the subset sum problem")
  Member "the parallel approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a scalable photonic computer solving the subset sum problem")

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.ET(Emerging Technologies)