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CVPR
2011
IEEE
14 years 9 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
IADIS
2003
15 years 2 months ago
Hypertext Classification: A Multiagent Model for Adaptive Learning Algorithm
The problem of hypertext classification deals with objects possessing more complex information structure than the plain text has. Present hypertext classification systems show the...
Stanislav Baglei
ICML
2009
IEEE
16 years 2 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
CVPR
2009
IEEE
1002views Computer Vision» more  CVPR 2009»
16 years 8 months ago
Classifier Grids for Robust Adaptive Object Detection
In this paper we present an adaptive but robust object detector for static cameras by introducing classifier grids. Instead of using a sliding window for object detection we pro...
Peter M. Roth, Sabine Sternig, Helmut Grabner, Hor...
AVSS
2006
IEEE
15 years 7 months ago
An Online Discriminative Approach to Background Subtraction
We present a simple, principled approach to detecting foreground objects in video sequences in real-time. Our method is based on an on-line discriminative learning technique that ...
Li Cheng, Shaojun Wang, Dale Schuurmans, Terry Cae...