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» Relevance Ranking Using Kernels
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WWW
2008
ACM
16 years 4 months ago
First workshop on targeting and ranking for online advertising
Online advertising is a rapidly growing, multi-billion dollar industry. It has become a significant element of the Web browsing experience. Ad platforms used for ad selection use ...
Ewa Dominowska, Vanja Josifovski
116
Voted
ECIR
2009
Springer
16 years 14 days ago
Risk-Aware Information Retrieval
Probabilistic retrieval models usually rank documents based on a scalar quantity. However, such models lack any estimate for the uncertainty associated with a document’s rank. Fu...
Jianhan Zhu, Jun Wang, Michael J. Taylor, Ingemar ...
152
Voted
ML
2002
ACM
163views Machine Learning» more  ML 2002»
15 years 2 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
164
Voted
SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
13 years 5 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
SNPD
2003
15 years 4 months ago
Categorization of Transparent-Motion Patterns Using the Projective Plane
Based on a new framework for the description of N transparent motions we categorize different types of transparent-motion patterns. Confidence measures for the presence of all th...
Cicero Mota, Michael Dorr, Ingo Stuke, Erhardt Bar...