Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
In this work, we present an active-learning algorithm for piecewise planar 3D reconstruction of a scene. While previous interactive algorithms require the user to provide tedious i...
Adarsh Kowdle, Yao-Jen Chang, Andrew Gallagher, Ts...
Accurate estimation and tracking of dynamic tissue deformation is important to motion compensation, intra-operative surgical guidance and navigation in minimally invasive surgery. ...
Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active ...