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ICCV
2011
IEEE
12 years 7 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
ICDM
2009
IEEE
124views Data Mining» more  ICDM 2009»
13 years 5 months ago
A Practical Differentially Private Random Decision Tree Classifier
In this paper, we study the problem of constructing private classifiers using decision trees, within the framework of differential privacy. We first construct privacy-preserving ID...
Geetha Jagannathan, Krishnan Pillaipakkamnatt, Reb...
CVPR
2011
IEEE
13 years 3 months ago
Combining Randomization and Discrimination for Fine-Grained Image Categorization
In this paper, we study the problem of fine-grained image categorization. The goal of our method is to explore fine image statistics and identify the discriminative image patche...
Bangpeng Yao, Aditya Khosla, Li Fei-Fei
IEEEPACT
2007
IEEE
14 years 1 months ago
Automatic Correction of Loop Transformations
Loop nest optimization is a combinatorial problem. Due to the growing complexity of modern architectures, it involves two increasingly difficult tasks: (1) analyzing the profita...
Nicolas Vasilache, Albert Cohen, Louis-Noël P...
TSP
2008
151views more  TSP 2008»
13 years 7 months ago
Convergence Analysis of Reweighted Sum-Product Algorithms
Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...