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ICCV
2011
IEEE
14 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
218
Voted
PPOPP
2012
ACM
14 years 2 months ago
Massively parallel breadth first search using a tree-structured memory model
Analysis of massive graphs has emerged as an important area for massively parallel computation. In this paper, it is shown how the Fresh Breeze trees-of-chunks memory model may be...
Tom St. John, Jack B. Dennis, Guang R. Gao
266
Voted
MOBIHOC
2012
ACM
13 years 9 months ago
Channel width assignment using relative backlog: extending back-pressure to physical layer
With recent advances in Software-defined Radios (SDRs), it has indeed became feasible to dynamically adapt the channel widths at smaller time scales. Even though the advantages o...
Parth H. Pathak, Sankalp Nimbhorkar, Rudra Dutta
CVPR
2012
IEEE
13 years 9 months ago
Large scale metric learning from equivalence constraints
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Martin Köstinger, Martin Hirzer, Paul Wohlhar...
228
Voted
ICAC
2006
IEEE
16 years 1 months ago
Weatherman: Automated, Online and Predictive Thermal Mapping and Management for Data Centers
— Recent advances have demonstrated the potential benefits of coordinated management of thermal load in data centers, including reduced cooling costs and improved resistance to ...
Justin D. Moore, Jeffrey S. Chase, Parthasarathy R...