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» Object correspondence as a machine learning problem
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CORR
2010
Springer
103views Education» more  CORR 2010»
14 years 11 months ago
On the Finite Time Convergence of Cyclic Coordinate Descent Methods
Cyclic coordinate descent is a classic optimization method that has witnessed a resurgence of interest in machine learning. Reasons for this include its simplicity, speed and stab...
Ankan Saha, Ambuj Tewari
ICCV
2009
IEEE
14 years 9 months ago
Realtime background subtraction from dynamic scenes
This paper examines the problem of moving object detection. More precisely, it addresses the difficult scenarios where background scene textures in the video might change over tim...
Li Cheng, Minglun Gong
COMPGEOM
2011
ACM
14 years 3 months ago
Comparing distributions and shapes using the kernel distance
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
SEMWEB
2010
Springer
14 years 9 months ago
Supporting Natural Language Processing with Background Knowledge: Coreference Resolution Case
Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
Volha Bryl, Claudio Giuliano, Luciano Serafini, Ka...
CVPR
2009
IEEE
16 years 6 months ago
Layered Graph Matching by Composite Cluster Sampling with Collaborative and Competitive Interactions
This paper studies a framework for matching an unknown number of corresponding structures in two images (shapes), motivated by detecting objects in cluttered background and lear...
Kun Zeng, Liang Lin, Song Chun Zhu, Xiaobai Liu