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Optimization Algorithms for Data Analysis

Module code: CS7DS2 · Semester: Semester 2

Questions by Year​

0 of 2 done · tick papers and add notes as you go

Papers open on tcd.ie (sign in to TCD first).

Topics

  • Gradient descent variants: Adam, Adagrad, RMSprop, Polyak momentum, Nesterov LO1–2
  • Stochastic and mini-batch gradient descent LO2–3
  • Constraints: projected gradient descent, penalty methods, Frank-Wolfe LO2
  • Gradient-free methods and hyperparameter optimisation LO2–3
Learning outcomes
  1. Identify optimisation problems in data analysis and machine learning
  2. Evaluate and design practical optimisation algorithms for ML
  3. Compare algorithms on speed, complexity and scalability

Summarised from the module descriptor, checked November 2026.