The P-norm push: A simple convex ranking algorithm that concentrates at the top of the list
We are interested in supervised ranking algorithms that perform especially well near the top of the ranked list, and are only required to perform sufficiently well on the rest of the list. In this work, we provide a general form of convex objective that gives high-scoring examples more importance. This "push" near the top of the list can be chosen arbitrarily large or small, based on the preference of the user. We choose ℓ
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- Artificial Intelligence & Image Processing
- 4905 Statistics
- 4611 Machine learning
- 17 Psychology and Cognitive Sciences
- 08 Information and Computing Sciences
Citation
Published In
EISSN
ISSN
Publication Date
Volume
Start / End Page
Related Subject Headings
- Artificial Intelligence & Image Processing
- 4905 Statistics
- 4611 Machine learning
- 17 Psychology and Cognitive Sciences
- 08 Information and Computing Sciences