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SIAMJO
2011
14 years 8 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
16 years 3 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
16 years 2 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 7 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
15 years 3 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