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Direct Optimization of IR Metrics


A Support Vector Method for Optimizing Average Precision  Yisong Yue, Thomas Finley, Filip Radlinski, Thorsten Joachims
BagBoo: A Scalable Hybrid Bagging-the-Boosting Model  Dmitry Pavlov, Alexey Gorodilov, Cliff Brun
CS646: Information Retrieval Lecture 16: Learning-to-rank  Jiepu Jiang
Dynamic Bayesian Network Click Model for Web Search Ranking  Olivier Chapelle, Ya Zhang
Early Exit Optimizations for Additive Machine Learned Ranking Systems  Barla Cambazoglu, Hugo Zaragoza, Olivier Chapelle, Jiang Chen, Ciya Liao, Zhaohui Zheng
Efficient Algorithms for Ranking with SVMs  O. Chapelle, S. S. Keerthi
Future directions in learning to rank  Olivier Chapelle, Yi Chang, Tie-Yan Liu
Large Scale Learning to Rank  D. Sculley
Learning in a Pairwise Term-Term Proximity Framework for Information Retrieval  Ronan Cummins, Colm O’Riordan
Learning to rank  Andrew Trotman
Learning to Rank (ACML 2009 tutorial)  Hang Li
Learning to Rank for Information Retrieval (WWW2009 tutorial)   - Learning to rank tutorial
Learning to Rank using Gradient Descent  Chris Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, Greg Hullende
Learning to rank: from pairwise approach to listwise approach  Z Cao, T Qin, TY Liu, MF Tsai, Hang Li
Lerot: an Online Learning to Rank Framework.  A. Schuth, K. Hofmann, S. Whiteson, M. de Rijke
Optimizing Search Engines Using Clickthrough Data  Thorsten Joachims
SVM Tutorial: Classification, Regression, and Ranking  Hwanjo Yu, Sungchul Kim
Using gradient descent to optimize language modeling smoothing parameters  Donald Metzler
Web-Search Ranking with Initialized Gradient Boosted Regression Trees  Ananth Mohan, Zheng Chen, Kilian Weinberge
Winning The Transfer Learning Track of Yahoo!  Andrey Gulin, Igor Kuralenok, Dmitry Pavlov
Yahoo! Learning to Rank Challenge Overview  Olivier Chapelle, Yi Chan