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CVPR
2011
IEEE
15 years 1 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell
ADC
2010
Springer
214views Database» more  ADC 2010»
15 years 1 months ago
Building a dynamic classifier for large text data collections
Due to the lack of in-built tools to navigate the web, people have to use external solutions to find information. The most popular of these are search engines and web directories....
Pavel Kalinov, Bela Stantic, Abdul Sattar
JMLR
2010
124views more  JMLR 2010»
15 years 1 months ago
Multiclass-Multilabel Classification with More Classes than Examples
We discuss multiclass-multilabel classification problems in which the set of classes is extremely large. Most existing multiclass-multilabel learning algorithms expect to observe ...
Ofer Dekel, Ohad Shamir
ML
2010
ACM
138views Machine Learning» more  ML 2010»
15 years 1 months ago
Mining adversarial patterns via regularized loss minimization
Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is...
Wei Liu, Sanjay Chawla
CVPR
2011
IEEE
14 years 10 months ago
Robust Tracking Using Local Sparse Appearance Model and K-Selection
Online learned tracking is widely used for it’s adaptive ability to handle appearance changes. However, it introduces potential drifting problems due to the accumulation of erro...
Baiyang Liu, junzhou Huang, Casimir Kulikowski, Li...