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: "typing linear algebra a biproduct oriented approach"
  Abstract: Interested in formalizing the generation of fast running code for linear algebra applications, the authors show how an index-free, calculational approach to matrix algebra can be developed by regarding matrices as morphisms of a category with biproducts. This shifts the traditional view of matrices as indexed structures to a type-level perspective analogous to that of the pointfree algebra of programming. The derivation of fusion, cancellation and abide laws from the biproduct equations makes it easy to calculate algorithms implementing matrix multiplication, the central operation of matrix algebra, ranging from its divide-and-conquer version to its vectorization implementation. From errant attempts to learn how particular products and coproducts emerge from biproducts, not only blocked matrix algebra is rediscovered but also a way of extending other operations (e.g. Gaussian elimination) blockwise, in a calculational style, is found. The prospect of building biproduct-based type checkers for computer algebra systems such as MatlabTM is also considered.

Connected through hyperedge HE-1 (induced by source paper "a compositional framework for scientific model augmentation"):
  with members:
    - "teaching machines to understand data science code by semantic enrichment of dataflow graphs"
    - "julia a fresh approach to numerical computing"
    - "best practices for scientific computing"
    - "ologs a categorical framework for knowledge representation"

Connected through hyperedge HE-2 (induced by source paper "the simple essence of automatic differentiation"):
  with members:
    - "tensorflow a system for large scale machine learning"
    - "caffe convolutional architecture for fast feature embedding"

Connected through hyperedge HE-3 (induced by source paper "typed linear algebra for efficient analytical querying"):
  with members:
    - "column oriented storage techniques for mapreduce"

Connected through hyperedge HE-4 (induced by source paper "strongly typed recurrent neural networks"):
  with members:
    - "lstm a search space odyssey"
    - "a simple way to initialize recurrent networks of rectified linear units"
    - "acdc a structured efficient linear layer"
    - "batch normalization accelerating deep network training by reducing internal covariate shift"
    - "learning to transduce with unbounded memory"
    - "visualizing and understanding recurrent networks"
    - "draw a recurrent neural network for image generation"
    - "neural turing machines"

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.SE(Software Engineering)