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» Application of Reduce Order Modeling to Time Parallelization
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SIGIR
2012
ACM
13 years 5 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
CACM
1998
103views more  CACM 1998»
15 years 2 months ago
The Virtual Design Team
The long range goal of the “Virtual Design Team” (VDT) research program is to develop computational tools to analyze decision making and communication behavior and thereby to ...
John C. Kunz, Tore R. Christiansen, Geoff P. Cohen...
CORR
2006
Springer
153views Education» more  CORR 2006»
15 years 3 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
HPDC
2007
IEEE
15 years 9 months ago
A statistical approach to risk mitigation in computational markets
We study stochastic models to mitigate the risk of poor Quality-of-Service (QoS) in computational markets. Consumers who purchase services expect both price and performance guaran...
Thomas Sandholm, Kevin Lai
WCE
2007
15 years 4 months ago
Sparse Matrix Multiplication Using UPC
—Partitioned global address space (PGAS) languages, such as Unified Parallel C (UPC) have the promise of being productive. Due to the shared address space view that they provide,...
Hoda El-Sayed, Eric Wright