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» Learning and Inference with Constraints
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MVA
2007
160views Computer Vision» more  MVA 2007»
15 years 7 months ago
Probabilistic Motion Segmentation of Videos for Temporal Super Resolution
A novel scheme is proposed for achieving motion segmentation in low-frame rate videos, with application to temporal super resolution. Probabilistic generative models are commonly ...
Arasanathan Thayananthan, Masahiro Iwasaki, Robert...
ICML
2010
IEEE
15 years 7 months ago
Finding Planted Partitions in Nearly Linear Time using Arrested Spectral Clustering
We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high pro...
Nader H. Bshouty, Philip M. Long
ICML
2010
IEEE
15 years 7 months ago
Robust Formulations for Handling Uncertainty in Kernel Matrices
We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we ...
Sahely Bhadra, Sourangshu Bhattacharya, Chiranjib ...
CVPR
2010
IEEE
15 years 6 months ago
Deconvolutional networks
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylo...
CORR
2010
Springer
70views Education» more  CORR 2010»
15 years 6 months ago
Structured sparsity-inducing norms through submodular functions
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
Francis Bach