< Parameter Estimation for Application Executions on Approximate Computing Hardware

---

Approximate Computing for Support Vector Machines

13:45 - 14:30, Hotel Zollernblick, Freudenstadt, Dr. Claus Braun, Institut für Technische Informatik

---

Support Vector Machines are supervised learning models with associated learning algorithms that analyse data used for classification and regression analysis. As a central component of modern machine learning, Support Vector Machines are widely used as effective classifiers for linear and nonlinear problems. This presentation looks at the use of Support Vector machines in the context of Approximate Computing.