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» Learning algorithms for online principal-agent problems (and...
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ICCV
2009
IEEE
13 years 5 months ago
A robust boosting tracker with minimum error bound in a co-training framework
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
Rong Liu, Jian Cheng, Hanqing Lu
PKDD
2005
Springer
164views Data Mining» more  PKDD 2005»
14 years 25 days ago
Clustering and Prediction of Mobile User Routes from Cellular Data
Location-awareness and prediction of future locations is an important problem in pervasive and mobile computing. In cellular systems (e.g., GSM) the serving cell is easily availabl...
Kari Laasonen
ASC
2006
13 years 8 months ago
Simulation-based optimisation using local search and neural network metamodels
This paper presents a new algorithm for enhancing the efficiency of simulation-based optimisation using local search and neural network metamodels. The local search strategy is ba...
Anna Persson, Henrik Grimm, Amos Ng
ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
13 years 11 months ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo
WWW
2008
ACM
14 years 8 months ago
Using the wisdom of the crowds for keyword generation
In the sponsored search model, search engines are paid by businesses that are interested in displaying ads for their site alongside the search results. Businesses bid for keywords...
Ariel Fuxman, Panayiotis Tsaparas, Kannan Achan, R...