Ou descente de gradient stochastique en français.
(à venir)
Lectures
Adam: A Method for Stochastic Optimization
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
Sparse Online Learning via Truncated Gradient
Stabilized Sparse Online Learning for Sparse Data
On Perturbed Proximal Gradient Algorithms
Large Margin Classification Using the Perceptron Algorithm
Scaling Up Stochastic Dual Coordinate Ascent
Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization
Dual Principal Component Pursuit
Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification
Compact Convex Projections
Optimization Methods for Large-Scale Machine Learning
k-SVRG: Variance Reduction for Large Scale Optimization
Accelerating Stochastic Gradient Descent using Predictive Variance Reduction
