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» Generation of Attributes for Learning Algorithms
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SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 2 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
IQIS
2004
ACM
14 years 2 months ago
Mining for Patterns in Contradictory Data
Information integration is often faced with the problem that different data sources represent the same set of the real-world objects, but give conflicting values for specific prop...
Heiko Müller, Ulf Leser, Johann Christoph Fre...
CVPR
2012
IEEE
11 years 11 months ago
A codebook-free and annotation-free approach for fine-grained image categorization
Fine-grained categorization refers to the task of classifying objects that belong to the same basic-level class (e.g. different bird species) and share similar shape or visual app...
Bangpeng Yao, Gary R. Bradski, Fei-Fei Li
IJCNN
2008
IEEE
14 years 3 months ago
Active Meta-Learning with Uncertainty Sampling and Outlier Detection
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...
AMAI
1999
Springer
13 years 8 months ago
Maintenance scheduling problems as benchmarks for constraint algorithms
The paper focuses on evaluating constraint satisfaction search algorithms on application based random problem instances. The application we use is a well-studied problem in the el...
Daniel Frost, Rina Dechter