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» Learning to Optimize Plan Execution in Information Agents
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AAAI
2006
13 years 10 months ago
An Efficient Algorithm for Local Distance Metric Learning
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...
Liu Yang, Rong Jin, Rahul Sukthankar, Yi Liu
SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
14 years 2 months ago
An improved immune Q-learning algorithm
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
IBPRIA
2009
Springer
14 years 1 months ago
Inference and Learning for Active Sensing, Experimental Design and Control
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Hendrik Kück, Matthew Hoffman, Arnaud Doucet,...
CIKM
2005
Springer
14 years 2 months ago
Selectivity-based partitioning: a divide-and-union paradigm for effective query optimization
Modern query optimizers select an efficient join ordering for a physical execution plan based essentially on the average join selectivity factors among the referenced tables. In ...
Neoklis Polyzotis
SAC
2010
ACM
14 years 3 months ago
A business driven cloud optimization architecture
In this paper, we discuss several facets of optimization in cloud computing, the corresponding challenges and propose an architecture for addressing those challenges. We consider ...
Marin Litoiu, C. Murray Woodside, Johnny Wong, Joa...