Logistic Regression: Tight Bounds for Stochastic and Online Optimization
Published on Jul 15, 20142343 Views
The logistic loss function is often advocated in machine learning and statistics as a smooth and strictly convex surrogate for the 0-1 loss. In this paper we investigate the question of whether these