Machine Learning for AC Optimal Power Flow

no code implementations • 19 Oct 2019 • Neel Guha, Zhecheng Wang, Matt Wytock, Arun Majumdar

We explore machine learning methods for AC Optimal Powerflow (ACOPF) - the task of optimizing power generation in a transmission network according while respecting physical and engineering constraints.

BIG-bench Machine Learning

Probabilistic Segmentation via Total Variation Regularization

no code implementations • 16 Nov 2015 • Matt Wytock, J. Zico Kolter

We present a convex approach to probabilistic segmentation and modeling of time series data.

Density Estimation Segmentation +2

Contextually Supervised Source Separation with Application to Energy Disaggregation

no code implementations • 18 Dec 2013 • Matt Wytock, J. Zico Kolter

We propose a new framework for single-channel source separation that lies between the fully supervised and unsupervised setting.