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NIPS
2004
15 years 2 months ago
Computing regularization paths for learning multiple kernels
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
SC
2009
ACM
15 years 8 months ago
Lessons learned from a year's worth of benchmarks of large data clouds
In this paper, we discuss some of the lessons that we have learned working with the Hadoop and Sector/Sphere systems. Both of these systems are cloud-based systems designed to sup...
Yunhong Gu, Robert L. Grossman
ICCV
2011
IEEE
14 years 1 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
CORR
2010
Springer
89views Education» more  CORR 2010»
15 years 1 months ago
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm
We show that matrix completion with tracenorm regularization can be significantly hurt when entries of the matrix are sampled nonuniformly. We introduce a weighted version of the ...
Ruslan Salakhutdinov, Nathan Srebro