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» Linearizing Intuitionistic Implication
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UAI
2008
13 years 9 months ago
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Richard S. Sutton, Csaba Szepesvári, Alborz...
IOR
2006
177views more  IOR 2006»
13 years 7 months ago
Combinatorial Benders' Cuts for Mixed-Integer Linear Programming
Mixed-Integer Programs (MIP's) involving logical implications modelled through big-M coefficients, are notoriously among the hardest to solve. In this paper we propose and an...
Gianni Codato, Matteo Fischetti
SIAMIS
2011
13 years 2 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
VR
2009
IEEE
159views Virtual Reality» more  VR 2009»
14 years 2 months ago
Indoor vs. Outdoor Depth Perception for Mobile Augmented Reality
We tested users’ depth perception of virtual objects in our mobile augmented reality (AR) system in both indoor and outdoor environments using a depth matching task. The indoor ...
Mark A. Livingston, Zhuming Ai, J. Edward Swan II,...
CISS
2008
IEEE
14 years 2 months ago
Information theory based estimator of the number of sources in a sparse linear mixing model
—In this paper we present an Information Theoretic Estimator for the number of sources mutually disjoint in a linear mixing model. The approach follows the Minimum Description Le...
Radu Balan