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ICML
2005
IEEE
15 years 10 months ago
Learning to rank using gradient descent
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
SEKE
2007
Springer
15 years 4 months ago
An Approach to Software Testing of Machine Learning Applications
Some machine learning applications are intended to learn properties of data sets where the correct answers are not already known to human users. It is challenging to test such ML ...
Chris Murphy, Gail E. Kaiser, Marta Arias
CORR
2006
Springer
126views Education» more  CORR 2006»
14 years 10 months ago
Evaluating the Robustness of Learning from Implicit Feedback
This paper evaluates the robustness of learning from implicit feedback in web search. In particular, we create a model of user behavior by drawing upon user studies in laboratory ...
Filip Radlinski, Thorsten Joachims
PAMI
2012
13 years 12 days ago
IntentSearch: Capturing User Intention for One-Click Internet Image Search
—Web-scale image search engines (e.g. Google Image Search, Bing Image Search) mostly rely on surrounding text features. It is difficult for them to interpret users’ search int...
Xiaoou Tang, Ke Liu, Jingyu Cui, Fang Wen, Xiaogan...
ICSE
2003
IEEE-ACM
15 years 10 months ago
Quantifying the Value of Architecture Design Decisions: Lessons from the Field
This paper outlines experiences with using economic criteria to make architecture design decisions. It briefly describes the CBAM (Cost Benefit Analysis Method) framework applied ...
Mike Moore, Rick Kazman, Mark Klein, Jai Asundi