28 citations · 28 across the 2 of their papers we have counts for
4 papers
Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification
Jan Deriu, Aurelien Lucchi, Valeria De Luca +5
This paper presents a novel approach for multi-lingual sentiment classification in short texts. This is a challenging task as the amount of training data in languages other than En…
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy
Aryan Mokhtari, Alejandro Ribeiro
We consider empirical risk minimization for large-scale datasets. We introduce Ada Newton as an adaptive algorithm that uses Newton's method with adaptive sample sizes. The main id…
DynaNewton - Accelerating Newton's Method for Machine Learning
Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann
Newton's method is a fundamental technique in optimization with quadratic convergence within a neighborhood around the optimum. However reaching this neighborhood is often slow and…
A Variance Reduced Stochastic Newton Method
Aurelien Lucchi, Brian McWilliams, Thomas Hofmann
Quasi-Newton methods are widely used in practise for convex loss minimization problems. These methods exhibit good empirical performance on a wide variety of tasks and enjoy super-…