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ICCV
2011
IEEE
13 years 9 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»
15 years 10 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
15 years 1 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
14 years 11 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
12 years 12 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