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ICML
2008
IEEE
16 years 5 months ago
Optimizing estimated loss reduction for active sampling in rank learning
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of insta...
Pinar Donmez, Jaime G. Carbonell
ADMA
2008
Springer
151views Data Mining» more  ADMA 2008»
15 years 10 months ago
Link-Contexts for Ranking
Anchor text has been shown to be effective in ranking[6] and a variety of information retrieval tasks on web pages. Some authors have expanded on anchor text by using the words ar...
Jessica Gronski
128
Voted
AAAI
2007
15 years 6 months ago
Aggregating User-Centered Rankings to Improve Web Search
This paper is to investigate rank aggregation based on multiple user-centered measures in the context of the web search. We introduce a set of techniques to combine ranking lists ...
Lin Li, Zhenglu Yang, Masaru Kitsuregawa
IJCAI
2001
15 years 5 months ago
Active Learning for Class Probability Estimation and Ranking
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Maytal Saar-Tsechansky, Foster J. Provost
CORR
2011
Springer
209views Education» more  CORR 2011»
14 years 8 months ago
Analysis and Improvement of Low Rank Representation for Subspace segmentation
We analyze and improve low rank representation (LRR), the state-of-the-art algorithm for subspace segmentation of data. We prove that for the noiseless case, the optimization mode...
Siming Wei, Zhouchen Lin