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ICML
2008
IEEE
16 years 7 months ago
Listwise approach to learning to rank: theory and algorithm
This paper aims to conduct a study on the listwise approach to learning to rank. The listwise approach learns a ranking function by taking individual lists as instances and minimi...
Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, Ha...
NAACL
1994
15 years 7 months ago
A Report of Recent Progress in Transformation-Based Error-Driven Learning
Most recent research in trainable part of speech taggers has explored stochastic tagging. While these taggers obtain high accuracy, linguistic information is captured indirectly, ...
Eric Brill
AAAI
2012
13 years 9 months ago
A Testbed for Learning by Demonstration from Natural Language and RGB-Depth Video
We are developing a testbed for learning by demonstration combining spoken language and sensor data in a natural real-world environment. Microsoft Kinect RGBDepth cameras allow us...
Young Chol Song, Henry A. Kautz
FLAIRS
2008
15 years 8 months ago
Building Useful Models from Imbalanced Data with Sampling and Boosting
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
WSC
1998
15 years 7 months ago
Customer Interfacing - Lessons Learned
Customer interfacing is the process through which one works with and relates to their customer. Often in the technical world, modelers find it easier to interface with computers r...
David M. Ferrin, Richard P. Lavecchia