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» Embedding Heterogeneous Data Using Statistical Models
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132
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FAST
2009
15 years 3 days ago
A Framework for Fine-grained Data Integration and Curation, with Provenance, in a Dataspace
Some tasks in a dataspace (a loose collection of heterogeneous data sources) require integration of fine-grained data from diverse sources. This work is often done by end users kn...
David W. Archer, Lois M. L. Delcambre, David Maier
132
Voted
ISIPTA
2005
IEEE
140views Mathematics» more  ISIPTA 2005»
15 years 8 months ago
Conservative Rules for Predictive Inference with Incomplete Data
This paper addresses the following question: how should we update our beliefs after observing some incomplete data, in order to make credible predictions about new, and possibly i...
Marco Zaffalon
160
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CORR
2011
Springer
167views Education» more  CORR 2011»
14 years 9 months ago
Fast global convergence of gradient methods for high-dimensional statistical recovery
Many statistical M-estimators are based on convex optimization problems formed by the weighted sum of a loss function with a norm-based regularizer. We analyze the convergence rat...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
ASPLOS
2010
ACM
15 years 7 months ago
Modeling GPU-CPU workloads and systems
Heterogeneous systems, systems with multiple processors tailored for specialized tasks, are challenging programming environments. While it may be possible for domain experts to op...
Andrew Kerr, Gregory F. Diamos, Sudhakar Yalamanch...
116
Voted
BMCBI
2008
125views more  BMCBI 2008»
15 years 2 months ago
MAID : An effect size based model for microarray data integration across laboratories and platforms
Background: Gene expression profiling has the potential to unravel molecular mechanisms behind gene regulation and identify gene targets for therapeutic interventions. As microarr...
Ivan Borozan, Limin Chen, Bryan Paeper, Jenny E. H...