MIT Subject Listing & Schedule
Fall 2025 Search Results

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6.7250 Optimization for Machine Learning

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Not offered regularly; consult department
Prereq: 6.3900 and 18.06
Units: 3-0-9

Optimization algorithms are central to all of machine learning. Covers a variety of topics in optimization, with a focus on non-convex optimization. Focuses on both classical and cutting-edge results, including foundational topics grounded in convexity, complexity theory of first-order methods, stochastic optimization, as well as recent progress in non-Euclidean optimization, deep learning, and beyond. Prepares students to appreciate a broad spectrum of ideas in OPTML, learning to be not only informed users but also gaining exposure to research questions in the area.
Staff