Edinburgh Research Explorer

Prof Amos Storkey

Personal Chair of Machine Learning & Artifical Intelligence

  1. 2020
  2. BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget

    Turner, J., Crowley, E., O'Boyle, M., Storkey, A. & Gray, G., 1 Jan 2020, (Accepted/In press) Proceedings to the International Conference on Learning Representations 2020. 15 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  3. 2019
  4. Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs

    Radu, V., Kaszyk, J., Wen, Y., Turner, J., Cano, J., Crowley, E., Franke, B., Storkey, A. & O'Boyle, M., 15 Aug 2019, (Accepted/In press) 2019 IEEE International Symposium on Workload Characterization (IISWC). Institute of Electrical and Electronics Engineers (IEEE), 11 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  5. Exploration by random network distillation

    Burda, Y., Edwards, H., Storkey, A. & Klimov, O., 2019. 17 p.

    Research output: Contribution to conferencePaper

  6. How to train your MAML

    Antoniou, A., Edwards, H. & Storkey, A., 2019. 11 p.

    Research output: Contribution to conferencePaper

  7. Large-Scale Study of Curiosity-Driven Learning

    Burda, Y., Edwards, H., Pathak, D., Storkey, A., Darrell, T. & Efros, A. A., 2019. 15 p.

    Research output: Contribution to conferencePaper

  8. On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length

    Jastrzębski, S., Kenton, Z., Ballas, N., Fischer, A., Bengio, Y. & Storkey, A., 2019. 19 p.

    Research output: Contribution to conferencePaper

  9. 2018
  10. Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

    Turner, J., Cano Reyes, J., Radu, V., Crowley, E., O'Boyle, M. & Storkey, A., 13 Dec 2018, Proceedings of the - Workload Characterization (IISWC), 2018 IEEE International Symposium on. Raleigh, North Carolina, USA: Institute of Electrical and Electronics Engineers (IEEE), p. 101-110 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  11. Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio

    Jastrzębski, S., Kenton, Z., Arpit, D., Ballas, N., Fischer, A., Bengio, Y. & Storkey, A., Oct 2018, Proceedings of 27th International Conference on Artificial Neural Networks. Rhodes, Greece: Springer, Cham, p. 392-402 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  12. Augmenting Image Classifiers Using Data Augmentation Generative Adversarial Networks

    Antoniou, A., Storkey, A. & Edwards, H., 27 Sep 2018, Artificial Neural Networks and Machine Learning – ICANN 2018. Rhodes, Greece, p. 594-603 10 p. (Lecture Notes in Computer Science; vol. 11141).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  13. Moonshine: Distilling with Cheap Convolutions

    Crowley, E., Gray, G. & Storkey, A., 2018, Thirty-second Conference on Neural Information Processing Systems (NIPS 2018). Montreal, Canada, 11 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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