Key approaches in the rapidly developing area of sparse modeling, focusing on its application in fields including neuroscience, computational biology, and computer vision. Sparse …
An overview of recent work in the field of structured prediction, the building of predictive machine learning models for interrelated and dependent outputs.The goal of structured …
A description of perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees.In nearly all machine learning, …
Advances in computational geometry and machine learning that offer new methods for search, regression, and classification with large amounts of high-dimensional data. Regression …