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» Local and Global Complete Solution Learning Methods for QBF
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NIPS
2007
13 years 8 months ago
Multi-Task Learning via Conic Programming
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, ...
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
AROBOTS
2011
13 years 2 months ago
Large scale graph-based SLAM using aerial images as prior information
— To effectively navigate in their environments and accurately reach their target locations, mobile robots require a globally consistent map of the environment. The problem of le...
Rainer Kümmerle, Bastian Steder, Christian Do...
ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
13 years 6 months ago
Multiple relative pose graphs for robust cooperative mapping
Abstract— This paper describes a new algorithm for cooperative and persistent simultaneous localization and mapping (SLAM) using multiple robots. Recent pose graph representation...
Been Kim, Michael Kaess, Luke Fletcher, John J. Le...
ECCV
2008
Springer
14 years 9 months ago
Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Cassio Polpo de Campos, Yan Tong, Qiang Ji