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» Kernel Optimization in Discriminant Analysis
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NIPS
2001
13 years 9 months ago
On the Generalization Ability of On-Line Learning Algorithms
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
Nicolò Cesa-Bianchi, Alex Conconi, Claudio ...
GECCO
2007
Springer
124views Optimization» more  GECCO 2007»
13 years 11 months ago
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms
The Negative Slope Coefficient (nsc) is an empirical measure of problem hardness based on the analysis of offspring-fitness vs. parent-fitness scatterplots. The nsc has been teste...
Riccardo Poli, Leonardo Vanneschi
ISCAPDCS
2003
13 years 9 months ago
Performance Monitoring of N-tier Client/Server Systems
Despite the widespread deployment of client/server technology, there seem to be no tools currently available that are adequate for analyzing and tuning the performance of client/s...
Christoph Steigner, Jürgen Wilke
ICML
2010
IEEE
13 years 8 months ago
From Transformation-Based Dimensionality Reduction to Feature Selection
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
Mahdokht Masaeli, Glenn Fung, Jennifer G. Dy
VLSID
2009
IEEE
177views VLSI» more  VLSID 2009»
14 years 8 months ago
Accelerating System-Level Design Tasks Using Commodity Graphics Hardware: A Case Study
Many system-level design tasks (e.g. timing analysis, hardware/software partitioning and design space exploration) involve computational kernels that are intractable (usually NP-ha...
Unmesh D. Bordoloi, Samarjit Chakraborty