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ICML
2010
IEEE
15 years 7 months ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein
IJBRA
2007
80views more  IJBRA 2007»
15 years 6 months ago
On predicting secondary structure transition
A function of a protein is dependent on its structure; therefore, predicting a protein structure from an amino acid sequence is an active area of research. Optimally predicting a ...
Raja Loganantharaj, Vivek Philip

Book
5396views
17 years 5 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
ICML
2009
IEEE
16 years 7 months ago
A convex formulation for learning shared structures from multiple tasks
Multi-task learning (MTL) aims to improve generalization performance by learning multiple related tasks simultaneously. In this paper, we consider the problem of learning shared s...
Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye
GECCO
2005
Springer
112views Optimization» more  GECCO 2005»
15 years 12 months ago
Monotonic solution concepts in coevolution
Assume a coevolutionary algorithm capable of storing and utilizing all phenotypes discovered during its operation, for as long as it operates on a problem; that is, assume an algo...
Sevan G. Ficici