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CVPR
2010
IEEE
14 years 4 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
ICAART
2010
INSTICC
14 years 6 months ago
Complexity of Stochastic Branch and Bound Methods for Belief Tree Search in Bayesian Reinforcement Learning
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
Christos Dimitrakakis
ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
13 years 7 months ago
Learning Preferences with Millions of Parameters by Enforcing Sparsity
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
CIRA
2007
IEEE
147views Robotics» more  CIRA 2007»
14 years 3 months ago
Local Online Support Vector Regression for Learning Control
—Support vector regression (SVR) is a class of machine learning technique that has been successfully applied to low-level learning control in robotics. Because of the large amoun...
Younggeun Choi, Shin-Young Cheong, Nicolas Schweig...
WINE
2005
Springer
136views Economy» more  WINE 2005»
14 years 2 months ago
Click Fraud Resistant Methods for Learning Click-Through Rates
Abstract. In pay-per-click online advertising systems like Google, Overture, or MSN, advertisers are charged for their ads only when a user clicks on the ad. While these systems ha...
Nicole Immorlica, Kamal Jain, Mohammad Mahdian, Ku...