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ICML
1998
IEEE
16 years 3 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
BMCBI
2008
184views more  BMCBI 2008»
15 years 3 months ago
Integrating protein-protein interactions and text mining for protein function prediction
Background: Functional annotation of proteins remains a challenging task. Currently the scientific literature serves as the main source for yet uncurated functional annotations, b...
Samira Jaeger, Sylvain Gaudan, Ulf Leser, Dietrich...
IPPS
2009
IEEE
15 years 9 months ago
Exploring FPGAs for accelerating the phylogenetic likelihood function
Driven by novel biological wet lab techniques such as pyrosequencing there has been an unprecedented molecular data explosion over the last 2-3 years. The growth of biological seq...
Nikolaos Alachiotis, Euripides Sotiriades, Apostol...
GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
15 years 9 months ago
Evolution of functional specialization in a morphologically homogeneous robot
A central tenet of embodied artificial intelligence is that intelligent behavior arises out of the coupled dynamics between an agent’s body, brain and environment. It follows t...
Joshua S. Auerbach, Josh C. Bongard
BMCBI
2007
137views more  BMCBI 2007»
15 years 3 months ago
Bayesian refinement of protein functional site matching
Background: Matching functional sites is a key problem for the understanding of protein function and evolution. The commonly used graph theoretic approach, and other related appro...
Kanti V. Mardia, Vysaul B. Nyirongo, Peter J. Gree...