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» Machine learning problems from optimization perspective
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ECML
2007
Springer
15 years 9 months ago
Learning to Classify Documents with Only a Small Positive Training Set
Many real-world classification applications fall into the class of positive and unlabeled (PU) learning problems. In many such applications, not only could the negative training ex...
Xiaoli Li, Bing Liu, See-Kiong Ng
ICML
2009
IEEE
16 years 3 months ago
Large-scale deep unsupervised learning using graphics processors
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
Rajat Raina, Anand Madhavan, Andrew Y. Ng
CVPR
2010
IEEE
15 years 11 months ago
Optimizing One-Shot Recognition with Micro-Set Learning
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...
GECCO
2005
Springer
218views Optimization» more  GECCO 2005»
15 years 8 months ago
Particle swarm optimization for analysis of mass spectral serum profiles
Serum profiling using mass spectrometry is an emerging technology with a great potential to provide biomarkers for complex diseases such as cancer. However, protein profiles obtai...
Habtom W. Ressom, Rency S. Varghese, Daniel Saha, ...
ECSQARU
2005
Springer
15 years 8 months ago
Generating Fuzzy Models from Deep Knowledge: Robustness and Interpretability Issues
The most problematic and challenging issues in fuzzy modeling of nonlinear system dynamics deal with robustness and interpretability. Traditional data-driven approaches, especially...
Raffaella Guglielmann, Liliana Ironi