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Algorithm and architecture co-optimization

Programmable Data Parallel Accelerator for Mobile Computer Vision

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Authors:
Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela
Submitted On:
23 February 2016 - 1:44pm
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[1] Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela, "Programmable Data Parallel Accelerator for Mobile Computer Vision", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/361. Accessed: Sep. 21, 2019.
@article{361-15,
url = {http://sigport.org/361},
author = {Teemu Nyländen; Ilkka Hautala; Olli Silvén; Jari Hannuksela },
publisher = {IEEE SigPort},
title = {Programmable Data Parallel Accelerator for Mobile Computer Vision},
year = {2015} }
TY - EJOUR
T1 - Programmable Data Parallel Accelerator for Mobile Computer Vision
AU - Teemu Nyländen; Ilkka Hautala; Olli Silvén; Jari Hannuksela
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/361
ER -
Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela. (2015). Programmable Data Parallel Accelerator for Mobile Computer Vision. IEEE SigPort. http://sigport.org/361
Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela, 2015. Programmable Data Parallel Accelerator for Mobile Computer Vision. Available at: http://sigport.org/361.
Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela. (2015). "Programmable Data Parallel Accelerator for Mobile Computer Vision." Web.
1. Teemu Nyländen, Ilkka Hautala, Olli Silvén, Jari Hannuksela. Programmable Data Parallel Accelerator for Mobile Computer Vision [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/361

Practical Optimization Algorithms for Image Processing


Several problems in signal processing and machine learning can be casted as optimization problems. In many cases, they are of large-scale, nonlinear, have constraints, and nonsmooth in the unknown parameters. There exists plethora of fast algorithms for smooth convex optimization, but these algorithms are not readily applicable to nonsmooth problems, which has led to a considerable amount of research in this direction. In this paper, we propose a general algorithm for nonsmooth bound-constrained convex optimization problems.

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Authors:
Loic Denis, Eric Thiebaut, J-M Becker
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23 February 2016 - 1:43pm
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[1] Loic Denis, Eric Thiebaut, J-M Becker, "Practical Optimization Algorithms for Image Processing", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/223. Accessed: Sep. 21, 2019.
@article{223-15,
url = {http://sigport.org/223},
author = {Loic Denis; Eric Thiebaut; J-M Becker },
publisher = {IEEE SigPort},
title = {Practical Optimization Algorithms for Image Processing},
year = {2015} }
TY - EJOUR
T1 - Practical Optimization Algorithms for Image Processing
AU - Loic Denis; Eric Thiebaut; J-M Becker
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/223
ER -
Loic Denis, Eric Thiebaut, J-M Becker. (2015). Practical Optimization Algorithms for Image Processing. IEEE SigPort. http://sigport.org/223
Loic Denis, Eric Thiebaut, J-M Becker, 2015. Practical Optimization Algorithms for Image Processing. Available at: http://sigport.org/223.
Loic Denis, Eric Thiebaut, J-M Becker. (2015). "Practical Optimization Algorithms for Image Processing." Web.
1. Loic Denis, Eric Thiebaut, J-M Becker. Practical Optimization Algorithms for Image Processing [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/223

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