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Friday, September 14, 2018 1:00 pm - 1:00 pm EDT (GMT -04:00)

Master’s Thesis Presentation • Scientific Computation — Fast Algorithms for Finding the Characteristic Polynomial of a Rank 2 Drinfeld Module

Yossef Musleh, Master’s candidate
David R. Cheriton School of Computer Science

We introduce a Monte Carlo randomized algorithm for computing the characteristic polynomial of a rank 2 Drinfeld module than runs in $O(n^2 \log n \log \log n \log q)$ field operations. We also introduce a deterministic algorithm that runs in $O(n^{2.6258} \log n + n^2 \log n \log log n \log q)$ field operations. Both approaches are a significant improvement over the current literature.

Friday, September 21, 2018 1:30 pm - 1:30 pm EDT (GMT -04:00)

Master’s Thesis Presentation • Scientific Computation — Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation

Ahmed Khan, Master’s candidate
David R. Cheriton School of Computer Science

Neurobiologically-plausible learning algorithms for recurrent neural networks that can perform supervised learning are a neglected area of study. Equilibrium propagation is a recent synthesis of several ideas in biological and artificial neural network research that uses a continuous-time, energy-based neural model with a local learning rule. However, despite dealing with recurrent networks, equilibrium propagation has only been applied to discriminative categorization tasks.

Monday, September 24, 2018 3:30 pm - 3:30 pm EDT (GMT -04:00)

Inaugural Seminar • AI Institute — Artificial Intelligence — History, Opportunities and Challenges

Hamid Tizhoosh, SDE
University of Waterloo

The history of artificial intelligence (AI) contains several ebbs and flows and is marked by many colorful personalities. We review major milestones in the development of machine learning, starting from principal component analysis to deep networks, and point to a multitude of pivotal developments that have strongly contributed to drawing the historical path of AI.