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» Machine learning problems from optimization perspective
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KDD
2007
ACM
132views Data Mining» more  KDD 2007»
16 years 3 months ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
120
Voted
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
15 years 8 months ago
Extraction of informative genes from microarray data
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba
ICML
2002
IEEE
16 years 3 months ago
Multi-Instance Kernels
Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently, rese...
Adam Kowalczyk, Alex J. Smola, Peter A. Flach, Tho...
ICML
2010
IEEE
15 years 4 months ago
OTL: A Framework of Online Transfer Learning
In this paper, we investigate a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an online learning ...
Peilin Zhao, Steven C. H. Hoi
ICEIS
2010
IEEE
15 years 27 days ago
Pattern Recognition as a Human Centered non-Euclidean Problem
Regularities in the world are human defined. Patterns in the observed phenomena are there because we define and recognize them as such. Automatic pattern recognition tries to bridg...
Robert P. W. Duin