Marlos C. Machado

I am a research scientist at Google Brain in Montréal. I hold a Ph.D. from the University of Alberta where I worked with Michael Bowling and Marc G. Bellemare. My research interests lie broadly in Artificial Intelligence and particularly focus on Machine Learning/Reinforcement Learning.

[Google Scholar] [DBLP]

Marlos C. Machado

News

    • Dec: 2020: We had a paper accepted at Nature.
      • Autonomous Navigation of Stratospheric Balloons using Reinforcement Learning (w/ Bellemare, Candido, Castro, Gong, Moitra, Ponda, and Wang).
    • Sep: 2020: We had a paper accepted at NeurIPS’20.
      • An Operator View of Policy Gradient Methods (w/ Ghosh & Le Roux).
    • Aug: 2020: Our preprint is now available.
      • Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization (w/ Chung*, Thomas* & Le Roux).
    • Feb: 2020: I gave a talk at Stanford University.
      • Temporal Abstraction in RL with the Successor Representation.
    • Feb: 2020: I attended AAAI’20 in New York City.
    • Dec. 2019: We had two papers accepted at ICLR’20.
      • Exploration in Reinforcement Learning with Deep Covering Options (w/ Jinnai, Park, & Konidaris).
      • On Bonus Based Exploration Methods In The Arcade Learning Environment  (w/ Taiga, Fedus, Courville, & Bellemare).
    • Nov. 2019: We had a paper accepted at AAAI’20.
      • Count-Based Exploration with the Successor Representation (w/ Bellemare & Bowling).
    • Jul. 2019: I attended RLDM’19 in Montreal.
    • Mar. 2019: I started as a Research Scientist at Google Brain.