Matthew W. Hoffman

I’m a research scientist at Google DeepMind where I work primarily on reinforcement learning and sequential decision making problems.

Recent News

Recent Papers

Below are some recent preprints and publications. And while I try to keep this relatively up-to-date, it is almost inevitable that I fall behind. Check out my Google Scholar entry for more publications.

  1. Hoffman, M., Shahriari, B., Aslanides, J., Barth-Maron, G., Behbahani, F., Norman, T., Abdolmaleki, A., Cassirer, A., Yang, F., Baumli, K., Henderson, S., Novikov, A., Colmenarejo, S. G., Cabi, S., Gulcehre, C., Paine, T. L., Cowie, A., Wang, Z., Piot, B., and de Freitas, N. (2020). Acme: A Research Framework for Distributed Reinforcement Learning. arXiv:2006.00979. [pdf] [bibtex]

  2. Gu, A., Gulcehre, C., Paine, T. L., Hoffman, M., and Pascanu, R. (2019). Improving the Gating Mechanism of Recurrent Neural Networks. arXiv:1910.09890. [pdf] [bibtex]

  3. Paine, T. L., Gulcehre, C., Shahriari, B., Denil, M., Hoffman, M., Soyer, H., Tanburn, R., Kapturowski, S., Rabinowitz, N., Williams, D., Barth-Maron, G., Wang, Z., de Freitas, N., and Team, W. (2019). Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. arXiv:1909.01387. [pdf] [bibtex]