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» Level-set methods for convex optimization
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NIPS
2008
15 years 3 months ago
Clustered Multi-Task Learning: A Convex Formulation
In multi-task learning several related tasks are considered simultaneously, with the hope that by an appropriate sharing of information across tasks, each task may benefit from th...
Laurent Jacob, Francis Bach, Jean-Philippe Vert
ICCV
2007
IEEE
16 years 3 months ago
Global Optimization through Searching Rotation Space and Optimal Estimation of the Essential Matrix
This paper extends the set of problems for which a global solution can be found using modern optimization methods. In particular, the method is applied to estimation of the essent...
Richard I. Hartley, Fredrik Kahl
CIMAGING
2010
195views Hardware» more  CIMAGING 2010»
15 years 3 months ago
SPIRAL out of convexity: sparsity-regularized algorithms for photon-limited imaging
The observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Ga...
Zachary T. Harmany, Roummel F. Marcia, Rebecca Wil...
DAC
2004
ACM
16 years 2 months ago
Automated design of operational transconductance amplifiers using reversed geometric programming
We present a method for designing operational amplifiers using reversed geometric programming, which is an extension of geometric programming that allows both convex and non-conve...
Johan P. Vanderhaegen, Robert W. Brodersen
NIPS
2008
15 years 3 months ago
Tighter Bounds for Structured Estimation
Large-margin structured estimation methods minimize a convex upper bound of loss functions. While they allow for efficient optimization algorithms, these convex formulations are n...
Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexan...