Jun 15, 2016 · We propose AutoMOMML, an end-to-end, ML-based framework to build predictive models for objectives such as performance, and power.

We propose AutoMOMML, an end-to-end, machine-learning-based framework to build predictive models for objectives such as performance, power, and energy. The ...

The framework adopts statistical approaches to reduce the modeling complexity and automatically identifies and configures the most suitable learning algorithm ...

Publication. AutoMOMML: Automatic Multi-Objective Modeling with Machine Learning. Authors. Balaprakash, Prasanna; Tiwari, Ananta; Wild, Stefan; Carrington, ...

We propose AutoMOMML, an end-to-end, ML-based framework to build predictive models for objectives such as performance, and power. The framework adopts ...

We propose AutoMOMML, an end-to-end, ML-based framework to build predictive models for objectives such as performance, and power. The framework adopts ...

One of the major hardware/software research challenge. ▫ Unrealistic to expect application scientists to be experts in power optimization.

The framework adopts statistical approaches to reduce the modeling complexity and automatically identifies and configures the most suitable learning algorithm ...

AutoMOMML: Automatic multi-objective modeling with machine learning. Prasanna Balaprakash, Ananta Tiwari, Stefan M. Wild, Laura Carrington, Paul D. Hovland.

AutoMOMML: Automatic Multi-objective Modeling with Machine Learning. Prasanna Balaprakash, Ananta Tiwari, Stefan M. Wild, Laura Carrington, Paul D. Hovland ...