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https://www.cs.cornell.edu/people/tj/publications/yue_etal_07a.pdf
A Support Vector Method for Optimizing Average Precision Yisong Yue Cornell University Ithaca, NY, USA [email protected] Thomas Finley Cornell University
https://www.researchgate.net/publication/221300758_A_Support_Vector_Method_for_Optimizing_Average_Precision
A Support Vector Method for Optimizing Average Precision. ... A Suppor t V ector Method f or Optimizing A verage Precision. Yisong Y ue. ... tion o ver the vector differences of all relev an t ...
https://dl.acm.org/citation.cfm?id=1277790
Due to computational difficulties, few learning techniques have been developed to directly optimize for mean average precision (MAP), despite its widespread use in evaluating such systems. Existing approaches optimizing MAP either do not find a globally optimal …Cited by: 720
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.65.6413
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Machine learning is commonly used to improve ranked retrieval systems. Due to computational difficulties, few learning techniques have been developed to directly optimize for mean average precision (MAP), despite its widespread use in evaluating such systems. Existing approaches optimizing MAP either do not find a ...
http://citeseer.ist.psu.edu/showciting?cid=3925529
One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in information retrieval such as Mean Average Precision (MAP) and Normalized Discounted Cumulative Gain (NDCG).
https://dl.acm.org/purchase.cfm?id=1277790
Purchase this Article: A support vector method for optimizing average precision Yisong Yue, Thomas Finley, Filip Radlinski, Thorsten Joachims
https://www.semanticscholar.org/paper/A-support-vector-method-for-optimizing-average-Yue-Finley/094ce8379a16030a7a993b2f70af46916f7ea99b
Machine learning is commonly used to improve ranked retrieval systems. Due to computational difficulties, few learning techniques have been developed to directly optimize for mean average precision (MAP), despite its widespread use in evaluating such systems. Existing approaches optimizing MAP either do not find a globally optimal solution, or are computationally expensive. In contrast, we ...
https://www.researchgate.net/publication/281329532_Efficient_Optimization_for_Average_Precision_SVM
The accuracy of information retrieval systems is often measured using complex non-decomposable loss functions such as the average precision (AP) or the normalized discounted cumulative gain (NDCG).
http://projects.yisongyue.com/svmmap/
SVM map is a Support Vector Machine (SVM) algorithm for predicting rankings (of documents). It performs supervised learning using binary labeled training examples, with the goal of optimizing Mean Average Precision (MAP).
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.535.8300
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Machine learning is commonly used to improve ranked re-trieval systems. Due to computational difficulties, few learn-ing techniques have been developed to directly optimize for mean average precision (MAP), despite its widespread use in evaluating such systems.
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