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 "augmenting neural nets with symbolic synthesis applications to few shot learning"):
  Abstract: We propose symbolic learning as extensions to standard inductive learning models such as neural nets as a means to solve few shot learning problems. We device a class of visual discrimination puzzles that calls for recognizing objects and object relationships as well learning higher-level concepts from very few images. We propose a two-phase learning framework that combines models learned from large data sets using neural nets and symbolic first-order logic formulas learned from a few shot learning instance. We develop first-order logic synthesis techniques for discriminating images by using symbolic search and logic constraint solvers. By augmenting neural nets with them, we develop and evaluate a tool that can solve few shot visual discrimination puzzles with interpretable concepts.

Includes members:
  Member "houdini lifelong learning as program synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "automl zero evolving machine learning algorithms from scratch")
  Member "leveraging grammar and reinforcement learning for neural program synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improving molecular design by stochastic iterative target augmentation")
  Member "robustfill neural program learning under noisy i o":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")
  Member "neural sketch learning for conditional program generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning compositional rules via neural program synthesis")
  Member "learning to infer graphics programs from hand drawn images":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "unsupervised program synthesis for images using tree structured lstm")
  Member "differentiable programs with neural libraries":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "structural language models of code")
  Member "deepcoder learning to write programs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "automl zero evolving machine learning algorithms from scratch")
  Member "neuro symbolic program synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")

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.LG(Machine Learning)