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CVPR
2012
IEEE
13 years 9 months ago
A grammar for hierarchical object descriptions in logic programs
Modeling objects using formal grammars has recently regained much attention in computer vision. Probabilistic logic programming, such as Bilattice based Logical Reasoning (BLR), i...
Toufiq Parag, Claus Bahlmann, Vinay D. Shet, Manee...
CVPR
2012
IEEE
13 years 9 months ago
Complex loss optimization via dual decomposition
We describe a novel max-margin parameter learning approach for structured prediction problems under certain non-decomposable performance measures. Structured prediction is a commo...
Mani Ranjbar, Arash Vahdat, Greg Mori
FOCS
2009
IEEE
16 years 1 months ago
Symmetry and Approximability of Submodular Maximization Problems
Abstract— A number of recent results on optimization problems involving submodular functions have made use of the ”multilinear relaxation” of the problem [3], [8], [24], [14]...
Jan Vondrák
RECOMB
2005
Springer
16 years 7 months ago
Predicting Protein-Peptide Binding Affinity by Learning Peptide-Peptide Distance Functions
Many important cellular response mechanisms are activated when a peptide binds to an appropriate receptor. In the immune system, the recognition of pathogen peptides begins when th...
Chen Yanover, Tomer Hertz
RECOMB
2004
Springer
16 years 7 months ago
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...