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Automatic Curriculum Learning For Deep RL: A Short Survey
2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
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They can optimize domain randomization for Sim2Real transfer, organize task presentations in multi-task robotic settings, order sequences of opponents in multi-agent scenarios, etc. ...
Acknowledgments We have received funding for this work from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 817639). ...
Conclusion We applied Lagrangian decomposition to operator-counting heuristics and found that the multipliers correspond to partitioned cost functions. ...
doi:10.24963/ijcai.2020/663
dblp:conf/ijcai/PommereningRHCR20
fatcat:uazsfxe2lne4bljtm42moao6jq
Improved Constraint Propagation via Lagrangian Decomposition
[chapter]
2015
Lecture Notes in Computer Science
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We propose to improve the communication between constraints by introducing Lagrangian penalty costs between pairs of constraints, based on the Lagrangian decomposition scheme. ...
We apply this approach to constraints that can be represented by decision diagrams, and show that propagating Lagrangian cost information can help improve the overall bound computation as well as the solution ...
Conclusion We have introduced Lagrangian decomposition in the context of constraint programming as a generic approach to improve the constraint propagation process. ...
doi:10.1007/978-3-319-23219-5_3
fatcat:dfdzuvm2mbarjiz2narc77eik4
Lagrangian Decomposition via Sub-problem Search
[chapter]
2016
Lecture Notes in Computer Science
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In this paper, we propose a Lagrangian decomposition method where the sub-problems are solved via search rather than through a specialized propagator. ...
Recently, Lagrangian decomposition methods have been adapted and applied to Constraint Programming in order to yield stronger bounds on the objective function. ...
See [3] for more details.
Lagrangian Decomposition Lagrangian decomposition is a well understood application of Lagrangian relaxation in order to decompose an optimization problem into parts. ...
doi:10.1007/978-3-319-33954-2_6
fatcat:an6pfefpcfdjdlodcz7pzvpfee
Automated structure detection for distributed process optimization
2016
Computers and Chemical Engineering
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This paper presents two methodologies for optimal model-based decomposition, where an optimization problem is decomposed into several smaller sub-problems and subsequently solved by augmented Lagrangian ...
Largescale and highly nonlinear problems commonly arise in process optimization, and could greatly benefit from these approaches, as they reduce the storage requirements and computational costs for global ...
A. del Rio-Chanona would like to acknowledge CONACyT scholarship No. 522530 for funding this project. Author F. Fiorelli gratefully acknowledges the support from his family. The authors would also ...
doi:10.1016/j.compchemeng.2016.03.014
fatcat:pupohwsesfbbvo3fsii6ccc3a4
Segmenting Planar Superpixel Adjacency Graphs w.r.t. Non-planar Superpixel Affinity Graphs
[chapter]
2013
Lecture Notes in Computer Science
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We propose a relaxation by Lagrangian decomposition and a constrained set of re-parameterizations for which we can optimize exactly and efficiently. ...
We address the problem of segmenting an image into a previously unknown number of segments from the perspective of graph partitioning. ...
We propose a relaxation by Lagrangian decomposition and a constrained set of re-parameterizations for which we can optimize exactly and efficiently. ...
doi:10.1007/978-3-642-40395-8_20
fatcat:aqnhzo2vcfdwjd54go6xljhnaq
Page 8093 of Mathematical Reviews Vol. , Issue 99k
[page]
1999
Mathematical Reviews
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A fundamental problem in both Lagrangian relaxation and de- composition is the search for optimal Lagrange multipliers. ...
The authors review some fundamental results in Lagrangian re- laxation and decomposition as well as the optimization/separation equivalence implied by the ellipsoid algorithm. ...
A dual ascent heuristic for obtaining a lower bound of the generalized set partitioning problem with convexity constraints
2019
Discrete Optimization
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In this paper we propose a dual ascent heuristic for solving the linear relaxation of the generalized set partitioning problem with convexity constraints, which often models the master problem of a column ...
The proposed dual ascent heuristic is based on a reformulation and it uses Lagrangian relaxation and subgradient method. ...
Acknowledgement The authors would like to thank the anonymous reviewers and associate editor for their helpful suggestions. ...
doi:10.1016/j.disopt.2019.05.001
fatcat:bxswkzph55hp5obnyyl4z3ds64
Graph-Cut Rate Distortion Algorithm for Contourlet-Based Image Compression
2007
2007 IEEE International Conference on Image Processing
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We propose to apply this technique for rate-distortion Lagrangian optimization in subband image coding. ...
, like the contourlet decomposition. ...
In this paper we propose to apply this technique for rate-distortion Lagrangian optimization in subband image coding. ...
doi:10.1109/icip.2007.4379273
dblp:conf/icip/TrocanPF07
fatcat:mhudc2ltdfbrpkl2qw4yrof5jq
Impact of Power System Partitioning on the Efficiency of Distributed Multi-Step Optimization
[article]
2016
arXiv
pre-print
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The approach consists of a partitioning technique based on spectral clustering that determines the best system partition and an improved Optimality Condition Decomposition method that solves the optimization ...
Results of simulations conducted on the IEEE 14-bus and 118-bus systems show that the distributed MPC problem can be solved significantly faster by using a good partition of the system and this partition ...
Acknowledgment
325 The authors would like to thank ABB for the financial support and particularly Dr. Xiaoming Feng for his invaluable inputs. ...
arXiv:1606.00031v1
fatcat:mc2qox5lnbafxoxirwm4is6psm
Page 3556 of Mathematical Reviews Vol. , Issue 89F
[page]
1989
Mathematical Reviews
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This technique leads to the decomposable Lagrangian relax- ation (LD,) max{(f —u)x:Cx <d, x € X}+max{uy: Ay <b, ye Y}, which is called Lagrangian decomposition (LD). ...
For this purpose we describe a class of feasible partitions containing the -partitions, and discuss the problem of the existence of a regular truncation for such partitions. ...
Setting priorities: a new SPIHT-compatible algorithm for image compression
2000
Wavelet Applications in Signal and Image Processing VIII
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We introduce a new algorithm for progressive or multiresolution image compression. ...
The algorithm improves on the Set Partitioning in Hierarchical Trees (SPIlT) algorithm by replacing the SPIlT encoder. ...
We modify the SPIlT algorithm to allow for the inclusion of priority functions and the optimization of the given Lagrangian performance functional J. ...
doi:10.1117/12.408670
fatcat:nznvvvnlqverne6ozkpdx6txee
Block-based graph-cut rate allocation for subband image compression and transmission over wireless networks
2009
Proceedings of the 5th International Mobile Multimedia Communications Conference
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We propose to apply this technique for rate-distortion Lagrangian optimization in block-based subband image coding. ...
The compression of natural images and their transmission over multi-hop wireless networks still presents many challenges for the researchers and industry. ...
As the rate-distortion Lagrangian lies on a convex curve (i.e. D(R)), we propose to use the method in [7] for its optimization. ...
doi:10.4108/icst.mobimedia2009.7427
dblp:conf/mobimedia/TrocanPFY09
fatcat:tqazpeithfcpfcfjgpokuif5zu
Graph-Cut Rate-Distortion Optimization For Subband Image Compression
2007
Zenodo
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In this pa-per we propose to apply this technique for rate-distortion Lagrangian optimization in subband image coding. ...
As the rate-distortion Lagrangian lies on a convex decreasing curve (i.e. D(R)), we propose to use in the following this method for its optimization. ...
doi:10.5281/zenodo.40372
fatcat:t7rr6v632jg6poppdniv7wttzi
Benders decomposition approach to solve the capacitated facility location problem
[article]
2021
arXiv
pre-print
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In this paper, we implement the classic BD algorithm and some accelerating BD methods such as Pareto-optimality cut and L-shaped decomposition methods. ...
facilities and transportation costs, are minimized. ...
A great advantage of BD is that it converges straight to the optimal of the Mixed Integer Linear Program (MILP) rather than to a relaxation of the problem, as Dantzig-Wolfe decomposition and Lagrangian ...
arXiv:2104.10863v1
fatcat:iqgkux776vfrrmxeb77mebgxta
Multicommodity Network Flows: A Survey, Part II: Solution Methods
2018
International Journal of Operations Research
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Finally the computational performance of different solution methods in literature is compared and directions for future research are suggested. ...
paper to the previous one that focus on the MCNF applications and formulations, this paper first introduces the conventional MCNF solution methods such as price-directive, resourcedirective, and basis partitioning ...
Farvolden et al. (1993) partition the basis of the master problem using the arc-path form in DW decomposition. ...
doi:10.6886/ijor.201812_15(4).0002
doaj:6614b47a60864f25b944b6417a14e054
fatcat:3agaw3ax2jf6jjcikglnlzxrjy
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