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» Directly optimizing evaluation measures in learning to rank
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TREC
2008
14 years 11 months ago
Where to Stop Reading a Ranked List?
: We document our participation in the TREC 2008 Legal Track. This year we focused solely on selecting rank cut-offs for optimizing the given evaluation measure per topic.
Avi Arampatzis, Jaap Kamps
70
Voted
PAMI
2010
185views more  PAMI 2010»
14 years 8 months ago
Evaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality
—Stability (robustness) of feature selection methods is a topic of recent interest, yet often neglected importance, with direct impact on the reliability of machine learning syst...
Petr Somol, Jana Novovicová
NIPS
2007
14 years 11 months ago
On Ranking in Survival Analysis: Bounds on the Concordance Index
In this paper, we show that classical survival analysis involving censored data can naturally be cast as a ranking problem. The concordance index (CI), which quantifies the quali...
Vikas C. Raykar, Harald Steck, Balaji Krishnapuram...
CIKM
2009
Springer
14 years 7 months ago
Probabilistic models of ranking novel documents for faceted topic retrieval
Traditional models of information retrieval assume documents are independently relevant. But when the goal is retrieving diverse or novel information about a topic, retrieval mode...
Ben Carterette, Praveen Chandar
ICML
2009
IEEE
15 years 10 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel