Iterative Mthd Machine Learng (CS-0144)

Spring 2025 · CS 0144 · Tufts University · 3 credits · Undergraduate

Design and analysis of modern machine learning methods with emphasis on convex and nonconvex problems, and centralized, federated, and distributed computational architectures. Topics include convergence, complexities, contractions, fixed point theorems, and perturbation techniques; gradient descent and stochastic gradient descent in addition to accelerated methods including Polyak and Nesterov momentum, minibatching, and variance reduction. State of the practice methods will be covered including Adagrad, Autogard, Adam, sgdm with applications in image classification and document clustering. Recommendations: MATH 70 and CS 11

Course codes: CS-0144, CS 0144, CS0144, CS-144, CS 144, CS144, EE-0143, EE 0143, EE0143, EE-143, EE 143, EE143

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