This paper presents a new approach for time series prediction using local dynamic modeling. The proposed method is composed of three blocks: a Time Delay Line that transforms the o...
Next to prediction accuracy, the interpretability of models is one of the fundamental criteria for machine learning algorithms. While high accuracy learners have intensively been e...
We propose a fast 3D model acquisition system that aligns intensity and depth images, and reconstructs a textured 3D mesh. 3D views are registered with shape alignment based on in...
Louis-Philippe Morency, Ali Rahimi, Trevor Darrell
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
Abstract. While several powerful methods exist for automatically detecting symmetries in instances of constraint satisfaction problems (CSPs), current methods for detecting symmetr...