Current Semantic Role Labeling technologies are based on inductive algorithms trained over large scale repositories of annotated examples. Frame-based systems currently make use o...
Danilo Croce, Cristina Giannone, Paolo Annesi, Rob...
Total Variation (TV) regularization is a popular method for solving a wide variety of inverse problems in image processing. In order to optimize the reconstructed image, it is imp...
Abstract— There is a growing interest in building Internetscale sensor networks that integrate sensors from around the world into a single unified system. In contrast, robotics ...
Scalable similarity search is the core of many large scale learning or data mining applications. Recently, many research results demonstrate that one promising approach is creatin...
Modern life sciences research increasingly relies on computational solutions, from large scale data analyses to theoretical modeling. Within the theoretical models Boolean network...
: Large scale grids for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large s...
Nicolas Jacq, Vincent Breton, Hsin-Yen Chen, Li-Yu...
Simultaneous switching noise (SSN) has become an important issue in the design of the internal on-chip power distribution networks in current very large scale integration/ultra lar...
Large scale gene duplication is a major force driving the evolution of genetic functional innovation. Whole genome duplications are widely believed to have played an important rol...
Background: Coalescent simulations are playing a large role in interpreting large scale intraspecific sequence or polymorphism surveys and for planning and evaluating association ...
Thomas Mailund, Mikkel H. Schierup, Christian N. S...