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» Learning from Multiple Sources of Inaccurate Data
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NIPS
2007
15 years 5 months ago
The Tradeoffs of Large Scale Learning
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Léon Bottou, Olivier Bousquet
125
Voted
PVLDB
2008
110views more  PVLDB 2008»
15 years 3 months ago
DObjects: enabling distributed data services for metacomputing platforms
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...
Pawel Jurczyk, Li Xiong
144
Voted
EAGC
2004
Springer
15 years 9 months ago
Using Global Snapshots to Access Data Streams on the Grid
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...
Beth Plale
138
Voted
PROCEDIA
2010
103views more  PROCEDIA 2010»
14 years 10 months ago
Towards generating optimised finite element solvers for GPUs from high-level specifications
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...
Graham R. Markall, David A. Ham, Paul H. J. Kelly
154
Voted
IPM
2006
171views more  IPM 2006»
15 years 3 months ago
Automatic extraction of bilingual word pairs using inductive chain learning in various languages
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...
Hiroshi Echizen-ya, Kenji Araki, Yoshio Momouchi