In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
—Power consumption has emerged as the premier and most constraining aspect in modern microprocessor and application-specific designs. Gate sizing has been shown to be one of the...
Foad Dabiri, Ani Nahapetian, Miodrag Potkonjak, Ma...
Many state-of-the-art statistical parsers for English can be viewed as Probabilistic Context-Free Grammars (PCFGs) acquired from treebanks consisting of phrase-structure trees enri...
Current simulation-sampling techniques construct accurate model state for each measurement by continuously warming large microarchitectural structures (e.g., caches and the branch...
Thomas F. Wenisch, Roland E. Wunderlich, Babak Fal...
We report a comprehensive evaluation of the topological structure of protein-protein interaction (PPI) networks by mining and analyzing graphs constructed from the publicly availa...