Transfer Learning to Learn with Multitask Neural Model Search

Preprint English OPEN
Wong, Catherine; Gesmundo, Andrea;
(2017)
  • Subject: Statistics - Machine Learning | Computer Science - Artificial Intelligence | Computer Science - Learning

Deep learning models require extensive architecture design exploration and hyperparameter optimization to perform well on a given task. The exploration of the model design space is often made by a human expert, and optimized using a combination of grid search and search... View more
  • References (18)
    18 references, page 1 of 2

    Bowen Baker, Otkrist Gupta, Nikhil Naik, and Ramesh Raskar. Designing neural network architectures using reinforcement learning. arXiv preprint arXiv:1611.02167, 2016.

    Irwan Bello, Barret Zoph, Vijay Vasudevan, and Quoc V Le. Neural optimizer search with reinforcement learning. arXiv preprint arXiv:1709.07417, 2017.

    James Bergstra and Yoshua Bengio. Random search for hyper-parameter optimization. Journal of Machine Learning Research, 13(Feb):281-305, 2012.

    James Bergstra, Daniel Yamins, and David Cox. Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures. In International Conference on Machine Learning, pp. 115-123, 2013.

    Han Cai, Tianyao Chen, Weinan Zhang, Yong Yu, and Jun Wang. Reinforcement learning for architecture search by network transformation. arXiv preprint arXiv:1707.04873, 2017.

    David Vilares Calvo. Compositional language processing for multilingual sentiment analysis. PhD thesis, Universidade da Corun˜a, 2017.

    Fermın L Cruz, Jose A Troyano, Fernando Enriquez, and Javier Ortega. Clasificacio´n de documentos basada en la opinio´n: experimentos con un corpus de crıticas de cine en espanol. Procesamiento del lenguaje natural, 41:73-80, 2008.

    James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al. Overcoming catastrophic forgetting in neural networks. Proceedings of the National Academy of Sciences, pp. 201611835, 2017.

    Quoc V. Le and Tomas Mikolov. Distributed representations of sentences and documents. CoRR, abs/1405.4053, 2014. URL http://arxiv.org/abs/1405.4053.

    Andrew L Maas, Raymond E Daly, Peter T Pham, Dan Huang, Andrew Y Ng, and Christopher Potts. Learning word vectors for sentiment analysis. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies-Volume 1, pp. 142-150. Association for Computational Linguistics, 2011.

  • Related Organizations (7)
  • Metrics
Share - Bookmark