This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Many applications rely heavily on large amounts of data in the distributed storages collected over time or produced by large scale scientific experiments or simulations. The key co...
Data streams are a prevalent and growing source of timely data. As streams become more prevalent, richer interrogation of the contents of the streams are required. Value of the con...
We argue that producing maintainable high-performance implementations of finite element methods for multiple targets requires that they are written using a high-level domain-speci...
In this paper, we propose a new learning method for extracting bilingual word pairs from parallel corpora in various languages. In cross-language information retrieval, the system...