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» Efficient Model Selection for Kernel Logistic Regression
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CASES
2007
ACM
13 years 11 months ago
An efficient framework for dynamic reconfiguration of instruction-set customization
We present an efficient framework for dynamic reconfiguration of application-specific custom instructions. A key component of this framework is an iterative algorithm for temporal...
Huynh Phung Huynh, Joon Edward Sim, Tulika Mitra
AAI
2006
215views more  AAI 2006»
13 years 7 months ago
Extensive Evaluation of Efficient NLP-Driven Text Classification
Extensive experimental evidence is required to study the impact of text categorization approaches on real data and to assess the performance within operational scenarios. In this ...
Roberto Basili, Alessandro Moschitti, Maria Teresa...

Book
778views
15 years 5 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 5 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone
PLDI
2003
ACM
14 years 18 days ago
Bug isolation via remote program sampling
We propose a low-overhead sampling infrastructure for gathering information from the executions experienced by a program’s user community. Several example applications illustrat...
Ben Liblit, Alexander Aiken, Alice X. Zheng, Micha...