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SIAMJO
2011
14 years 4 months ago
A Unifying Polyhedral Approximation Framework for Convex Optimization
Abstract. We propose a unifying framework for polyhedral approximation in convex optimization. It subsumes classical methods, such as cutting plane and simplicial decomposition, bu...
Dimitri P. Bertsekas, Huizhen Yu
CVPR
2003
IEEE
15 years 11 months ago
Surfaces with Occlusions from Layered Stereo
Although steady progress has been made in recent stereo algorithms, producing accurate results in the neighborhood of depth discontinuities remains a challenge. Moreover, among th...
Michael H. Lin, Carlo Tomasi
ICML
2004
IEEE
15 years 10 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
MICCAI
2010
Springer
15 years 3 months ago
  A Fully Automated Approach to Segmentation of Irregularly Shaped Cellular Structures in EM Images
While there has been substantial progress in segmenting natural im- ages, state-of-the-art methods that perform well in such tasks unfortunately tend to underperform ...
A. Lucchi, K. Smith, R. Achanta, V. Lepetit, P. Fu...
COLING
2008
14 years 11 months ago
The Power of Negative Thinking: Exploiting Label Disagreement in the Min-cut Classification Framework
Treating classification as seeking minimum cuts in the appropriate graph has proven effective in a number of applications. The power of this approach lies in its ability to incorp...
Mohit Bansal, Claire Cardie, Lillian Lee