Preloader

Tag: AI

TIKHONOV OR LASSO REGULARIZATION: WHICH IS BETTER AND WHEN. IN TOOLS WITH ARTIFICIAL INTELLIGENCE

Fei Wang, Sanjay Chawla, and Wei Liu. “Tikhonov or lasso regularization: Which is better and when. In Tools with Artificial Intelligence” (ICTAI), 2013 IEEE 25th International Conference on, pages 795–802. IEEE, 2013. It is well known that supervised learning problems with ℓ1 (Lasso) and ℓ2 (Tikhonov or Ridge) regularizers will result in very different solutions. For example,

Read More

TIKHONOV OR LASSO REGULARIZATION: WHICH IS BETTER AND WHEN. IN TOOLS WITH ARTIFICIAL INTELLIGENCE

pages 795–802. IEEE, 2013. It is well known that supervised learning problems with ℓ1 (Lasso) and ℓ2 (Tikhonov or Ridge) regularizers will result in very different solutions. For example, the ℓ1 solution vector will be sparser and can potentially be used both for prediction and feature selection. However, given a data set it is often hard to determine

Read More

WHY THE BOARDS AND THE C-SUITE NEED TO BECOME DATA AND ANALYTICS SAVVY

Speaker: Roger Kermode (UTS) Seminar Date: Tuesday September 5 12:00pm Brief abstract: Recent research by the AIIA shows that many organisations are flying on auto-pilot when it comes to effectively using data and analytics for strategic purposes. Most of the effort locally in AI and Machine Learning focuses on operational and tactical issues which presents both risks (for incumbent

Read More