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The London Machine Learning Meetup is the largest machine learning community in Europe. Previous speakers include Juergen Schmidhuber, Yoshua Bengio and Andrej Karpathy.

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Alhussein Fawzi | Faster matrix multiplication with deep reinforcement learning

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Virtual London Machine Learning Meetup -[masked] @ 18:30 (UK)


  • 18:25: Virtual doors open
  • 18:30: Talk
  • 19:10: Q&A session
  • 19:30: Close

Sponsor: Evolution AI - Intelligent data extraction from corporate and financial documents.

Title: Discovering faster matrix multiplication algorithm with deep reinforcement learning

Speaker: Alhussein Fawzi, Research Scientist at DeepMind

Improving the efficiency of algorithms for fundamental computational tasks such as matrix multiplication can have widespread impact, as it affects the overall speed of a large amount of computations. The automatic discovery of algorithms using machine learning offers the prospect of reaching beyond human intuition and outperforming the current best human-designed algorithms.

In this talk I'll present AlphaTensor, our reinforcement learning agent based on AlphaZero for discovering efficient and provably correct algorithms for the multiplication of arbitrary matrices. AlphaTensor discovered algorithms that outperform the state-of-the-art complexity for many matrix sizes. Particularly relevant is the case of 4 × 4 matrices in a finite field, where AlphaTensor's algorithm improves on Strassen's two-level algorithm for the first time since its discovery 50 years ago. I'll present our problem formulation as a single-player game, the key ingredients that enable tackling such difficult mathematical problems using reinforcement learning, and the flexibility of the AlphaTensor framework.

Alhussein Fawzi is a research scientist in the Science team at DeepMind, where he leads the algorithmic discovery efforts. He is broadly interested in using machine learning to unlock new scientific discoveries. He obtained his PhD in machine learning and computer vision from EPFL in 2016.

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