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McGill.ca / Overview / Summer Studies / Areas of Study / Summer 2022 Courses

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MATH 562 Theory of Machine Learning (4 credits)

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Note: This is the 2021–2022 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .

Offered by: Mathematics and Statistics (Faculty of Science)

Overview

Mathematics & Statistics (Sci) : Concentration inequalities, PAC model, VC dimension, Rademacher complexity, convex optimization, gradient descent, boosting, kernels, support vector machines, regression and learning bounds. Further topics selected from: Gaussian processes, online learning, regret bounds, basic neural network theory.

Terms: Winter 2022

Instructors: Oberman, Adam (Winter)

  • Prerequisites: MATH 462 or COMP 451 or (COMP 551, MATH 222, MATH 223 and MATH 324) or ECSE 551.

  • Restrictions: Not open to students who have taken or are taking COMP 562. Not open to students who have taken COMP 599 when the topic was "Statistical Learning Theory" or "Mathematical Topics for Machine Learning". Not open to students who have taken COMP 598 when the topic was"Mathematical Foundations of Machine Learning".

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