We present a novel loop transformation technique, particularly well suited for optimizing embedded compilers, where an increase in compilation time is acceptable in exchange for s...
We describe an approach to extract attribute-value pairs from product descriptions. This allows us to represent products as sets of such attribute-value pairs to augment product d...
Katharina Probst, Rayid Ghani, Marko Krema, Andrew...
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
We present three systems for surface natural language generation that are trainable from annotated corpora. The first two systems, called NLG1 and NLG2, require a corpus marked on...
This paper describes a dynamic voltage and frequency scaling (DVFS) technique for MPEG decoding to reduce the energy consumption using the computational workload decomposition. Th...