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ICCV
2011
IEEE
12 years 5 months ago
Optical Flow Estimation Using Learned Sparse Model
Optical flow estimation is a fundamental and ill-posed problem in computer vision. To recover a dense flow field, appropriate spatial constraints have to be enforced. Recent ad...
Kui Jia, Xiaogang Wang, Xiaoou Tang
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 5 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang
ALT
2003
Springer
13 years 9 months ago
Efficiently Learning the Metric with Side-Information
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
Tijl De Bie, Michinari Momma, Nello Cristianini
HIS
2007
13 years 6 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
PAMI
2012
11 years 7 months ago
A Least-Squares Framework for Component Analysis
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
Fernando De la Torre