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MM
2004
ACM
124views Multimedia» more  MM 2004»
14 years 3 months ago
An online-optimized incremental learning framework for video semantic classification
This paper considers the problems of feature variation and concept uncertainty in typical learning-based video semantic classification schemes. We proposed a new online semantic c...
Jun Wu, Xian-Sheng Hua, HongJiang Zhang, Bo Zhang
ICCV
2011
IEEE
12 years 10 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
CVPR
2012
IEEE
12 years 24 days ago
Large scale metric learning from equivalence constraints
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Martin Köstinger, Martin Hirzer, Paul Wohlhar...
SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
14 years 4 months ago
An improved immune Q-learning algorithm
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
13 years 11 months ago
An evolutionary approach for competency-based curriculum sequencing
The process of creating e-learning contents using reusable learning objects (LOs) can be broken down in two sub-processes: LOs finding and LO sequencing. Sequencing is usually per...
Luis de Marcos, José-Javier Martínez...