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» On learning algorithm selection for classification
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ICML
2006
IEEE
16 years 7 months ago
Constructing informative priors using transfer learning
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
Rajat Raina, Andrew Y. Ng, Daphne Koller
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
16 years 7 months ago
On updates that constrain the features' connections during learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Jian Huang 0002
ML
2010
ACM
135views Machine Learning» more  ML 2010»
15 years 1 months ago
Multi-domain learning by confidence-weighted parameter combination
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Mark Dredze, Alex Kulesza, Koby Crammer
ICPR
2008
IEEE
16 years 7 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
NN
2007
Springer
15 years 6 months ago
From memory-based decisions to decision-based movements: A model of interval discrimination followed by action selection
The interval discrimination task is a classical experimental paradigm that is employed to study working memory and decision making and typically involves four phases. First, the s...
Prashant Joshi