Inaugural Seminar • AI Institute — Machine Learning for SAT Solvers
Vijay Ganesh, ECE
University of Waterloo
Vijay Ganesh, ECE
University of Waterloo
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.
Omar Zia Khan, Senior Applied Scientist
Microsoft
Pirathayini Srikantha, Department of Electrical and Computer Engineering
Western University
Finn Lidbetter, Master’s candidate
David R. Cheriton School of Computer Science
Let x and y be words. We consider the languages whose words z are those for which the numbers of occurrences of x and y, as subwords of z, are the same (resp., the number of x's is less than the number of y's, resp., is less than or equal). In this talk we will give a necessary and sufficient condition on x and y for these languages to be regular, and we show how to check this condition efficiently.
Matthew Amy, PhD candidate
David R. Cheriton School of Computer Science
Adam Molnar, Deakin University
Abdullah Rashwan, PhD candidate
David R. Cheriton School of Computer Science
Aiman Erbad, Computer Science and Engineering Department
Qatar University
Irfan Ahmad, Founder and CEO
CachePhysics
Caches in modern distributed and storage systems must be manually tuned and sized in response to changing application’s workload. A balance must be achieved between cost, performance and revenue loss from cache sizing mis-matches. However, caches are inherently nonlinear systems making this exercise equivalent to solving a maze in the dark.