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» On Online Learning of Decision Lists
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WWW
2009
ACM
14 years 7 months ago
Predicting click through rate for job listings
Click Through Rate (CTR) is an important metric for ad systems, job portals, recommendation systems. CTR impacts publisher's revenue, advertiser's bid amounts in "p...
Manish S. Gupta
ECCC
2007
180views more  ECCC 2007»
13 years 7 months ago
Adaptive Algorithms for Online Decision Problems
We study the notion of learning in an oblivious changing environment. Existing online learning algorithms which minimize regret are shown to converge to the average of all locally...
Elad Hazan, C. Seshadhri
ICPR
2008
IEEE
14 years 8 months ago
Human tracking based on Soft Decision Feature and online real boosting
Online Boosting is an effective incremental learning method which can update weak classifiers efficiently according to the object being trackedt. It is a promising technique for o...
Hironobu Fujiyoshi, Masato Kawade, Shihong Lao, Ta...
ITS
2010
Springer
160views Multimedia» more  ITS 2010»
13 years 11 months ago
The Online Deteriorating Patient: An Adaptive Simulation to Foster Expertise in Emergency Decision-Making
The deteriorating patient activity (DPA) is a low-fidelity educational simulation that prepares medical students to effectively approach emergency situations. This paper outlines h...
Emmanuel G. Blanchard, Jeffrey Wiseman, Laura Nais...
ORL
2007
66views more  ORL 2007»
13 years 6 months ago
Linear programming with online learning
We propose online decision strategies for time-dependent sequences of linear programs which use no distributional and minimal geometric assumptions about the data. These strategies...
Tatsiana Levina, Yuri Levin, Jeff McGill, Mikhail ...