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HIS
2007
13 years 9 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
JSA
2007
191views more  JSA 2007»
13 years 7 months ago
Automated memory-aware application distribution for Multi-processor System-on-Chips
Mapping of applications on a Multiprocessor System-on-Chip (MP-SoC) is a crucial step to optimize performance, energy and memory constraints at the same time. The problem is formu...
Heikki Orsila, Tero Kangas, Erno Salminen, Timo D....
BMCBI
2008
129views more  BMCBI 2008»
13 years 7 months ago
A unified approach to false discovery rate estimation
Background: False discovery rate (FDR) methods play an important role in analyzing highdimensional data. There are two types of FDR, tail area-based FDR and local FDR, as well as ...
Korbinian Strimmer
ALMOB
2007
151views more  ALMOB 2007»
13 years 7 months ago
Local sequence alignments statistics: deviations from Gumbel statistics in the rare-event tail
Background: The optimal score for ungapped local alignments of infinitely long random sequences is known to follow a Gumbel extreme value distribution. Less is known about the imp...
Stefan Wolfsheimer, Bernd Burghardt, Alexander K. ...
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 2 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang