We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbone...
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
Luca Baldassarre, Jean Morales, Andreas Argyriou, ...
: We present a new approach for computing generalized Voronoi diagrams in two and three dimensions using interpolation-based polygon rasterization hardware. The input primitives ma...
Kenneth E. Hoff III, Tim Culver, John Keyser, Ming...
We present an approach for solving the path planning problem for a mobile robot operating in an unknown, three dimensional environment containing obstacles of arbitrary shape. The...
Kiriakos N. Kutulakos, Vladimir J. Lumelsky, Charl...
Due to the intricate nature of the equation governing light transport in participating media, accurately and efficiently simulating radiative energy transfer remains very challeng...
Vincent Pegoraro, Mathias Schott, Steven G. Parker