December 21st1 module
An Introduction To Optimization Techniques In Machine Learning
Abstract
- From linear programming to non-convex smooth optimization
- Gradient descent
- Polyak's Heavy ball: accelerated gradient descent
- Stochastic gradient descent (SGD)
- SGD and Markov chains
- Variance reduced SGD
- Computational efficiency of SGD for statistical inference
- Computational statistical tradeoff through convex relaxation
Modules
Module 1: An Introduction To Optimization Techniques In Machine Learning (Hadi Daneshmand)Dec 21, 2017, 3:30 PM – 6:00 PM
Module 1: An Introduction To Optimization Techniques In Machine Learning (Hadi Daneshmand)Dec 21, 2017, 3:30 PM – 6:00 PM
Presenter
