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Automatic Curriculum Learning For Deep RL: A Short Survey

Rémy Portelas, Cédric Colas, Lilian Weng, Katja Hofmann, Pierre-Yves Oudeyer
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
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]

David Bergman, Andre A. Cire, Willem-Jan van Hoeve
2015 Lecture Notes in Computer Science  
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]

Geoffrey Chu, Graeme Gange, Peter J. Stuckey
2016 Lecture Notes in Computer Science  
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

Ehecatl Antonio del Rio-Chanona, Fabio Fiorelli, Vassilios S. Vassiliadis
2016 Computers and Chemical Engineering  
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]

Bjoern Andres, Julian Yarkony, B. S. Manjunath, Steffen Kirchhoff, Engin Turetken, Charless C. Fowlkes, Hanspeter Pfister
2013 Lecture Notes in Computer Science  
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  
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

Stefania Pan, Roberto Wolfler Calvo, Mahuna Akplogan, Lucas Létocart, Nora Touati
2019 Discrete Optimization  
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

M. Trocan, B. Pesquet-Popescu, J.E. Fowler
2007 2007 IEEE International Conference on Image Processing  
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]

Junyao Guo, Gabriela Hug, Ozan Tonguz
2016 arXiv   pre-print
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  
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

Diego Dugatkin, Michelle Effros, Akram Aldroubi, Andrew F. Laine, Michael A. Unser
2000 Wavelet Applications in Signal and Image Processing VIII  
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

Maria Trocan, Beatrice Pesquet-Popescu, James E. Fowler, Charles Yaacoub
2009 Proceedings of the 5th International Mobile Multimedia Communications Conference  
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

Maria Trocan, Beatrice Pesquet-Popescu
2007 Zenodo  
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]

Ali Akbar Sadat Asl, Ali Rouhani
2021 arXiv   pre-print
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

I-Lin Wang
2018 International Journal of Operations Research  
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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