no code implementations • NeurIPS 2017 • Kristofer E. Bouchard, Alejandro F. Bujan, Farbod Roosta-Khorasani, Shashanka Ubaru, Prabhat, Antoine M. Snijders, Jian-Hua Mao, Edward F. Chang, Michael W. Mahoney, Sharmodeep Bhattacharyya
The increasing size and complexity of scientific data could dramatically enhance discovery and prediction for basic scientific applications.
no code implementations • 10 Jun 2016 • Jesse A. Livezey, Alejandro F. Bujan, Friedrich T. Sommer
Further, by comparing ICA algorithms on synthetic data and natural images to the computationally more expensive sparse coding solution, we show that the coherence control biases the exploration of the data manifold, sometimes yielding suboptimal solutions.