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Learning Chordal Markov Networks via Branch and Bound
2017
Neural Information Processing Systems
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The algorithm is based on branch and bound and integrates dynamic programming for both domain pruning and for obtaining strong bounds for search-space pruning. ...
Empirically, we show that the approach dominates in terms of running times a recent integer programming approach (and thereby also a recent constraint optimization approach) for the problem. ...
Theorem 1 states that for any (partial) solution (i.e., an ordered decomposable DAG), there always exists an equivalent solution that does not contain any violations of the preferred vertex order. ...
dblp:conf/nips/RantanenHJ17
fatcat:rc43mc26cff73ljd6kmxmy2qfe
Hierarchical Bayesian optimization algorithm: toward a new generation of evolutionary algorithms
2006
ChoiceReviews
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To estimate the distribution, techniques for modeling multivariate data by Bayesian networks are used. The proposed algorithm identi es, reproduces and mixes building blocks up to a speci ed order. ...
Preliminary experiments show that the BOA outperforms the simple genetic algorithm even on decomposable functions with tight building blocks as a problem size grows. ...
Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any c o p yright notation thereon. ...
doi:10.5860/choice.43-2847
fatcat:w4llps6xwfdmzm7jol7jjxehpq
Page 805 of The Journal of the Operational Research Society Vol. 53, Issue 7
[page]
2002
The Journal of the Operational Research Society
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Consider a set of jobs N = {1 n} in EDD order where each of the jobs decomposes at only one position according to the optimal algorithm. ...
We then drew comparisons between the MDD rule and the optimal decomposition algorithm and demon- strated that their algorithmic structures have some striking similarities. ...
Markov-HTN Planning Approach to Enhance Flexibility of Automatic Web Service Composition
2009
2009 IEEE International Conference on Web Services
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Furthermore, an evaluation method to choose the optimal plan and some experimental results illustrate that the proposed approach works effectively. ...
In the model, HTN planning is enhanced to decompose a task in multiple ways and hence be able to find more than one plan, taking both functional and non-functional properties into account. ...
Acknowledgment Thanks to the anonymous reviewers for the comments ...
doi:10.1109/icws.2009.43
dblp:conf/icws/ChenXR09
fatcat:fxsybxwpcngaja5xjo3hbauv5y
Learning Bayesian networks with ancestral constraints
2016
Neural Information Processing Systems
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Our approach is based on a recently proposed framework for optimal structure learning based on non-decomposable scores, which is general enough to accommodate ancestral constraints. ...
The proposed framework exploits oracles for learning structures using decomposable scores, which cannot accommodate ancestral constraints since they are non-decomposable. ...
For example, DAG X → Y → Z expresses the same ancestral relations, after adding edge X → Z. ...
dblp:conf/nips/ChenSCD16
fatcat:heded6nw55g6pnrfqn3prvos3u
A Structural SVM Based Approach for Optimizing Partial AUC
2013
International Conference on Machine Learning
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optimization problem in the case of partial AUC is harder to decompose. ...
One of our key technical contributions is an efficient algorithm for solving this combinatorial optimization problem that has the same computational complexity as Joachims' algorithm for optimizing the ...
Thanks to the anonymous reviewers for helpful comments. HN thanks Microsoft Research India for a partial travel grant to attend the conference. ...
dblp:conf/icml/NarasimhanA13
fatcat:ngesxfc7evaqvp236ljsfhiq3e
Learning bayesian networks consistent with the optimal branching
2007
Sixth International Conference on Machine Learning and Applications (ICMLA 2007)
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The optimal branching is used as an heuristic for a primary causality order between network variables, which is subsequently refined, according to a certain score, into an optimal CkG Bayesian network. ...
The proposed algorithm can be applied to scores that decompose over the network structure, such as the well known LL, MDL, AIC, BIC, K2, BD, BDe, BDeu and MIT scores. ...
This work was partially supported by EU FEDER via FCT project POSC/EIA/ 57398/2004. ...
doi:10.1109/icmla.2007.74
dblp:conf/icmla/CarvalhoO07
fatcat:rdp53hwprbf4daj7nezufsezmy
A tutorial on decomposition methods for network utility maximization
2006
IEEE Journal on Selected Areas in Communications
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Finally, we present recent examples on: systematic search for alternative decompositions; decoupling techniques for coupled objective functions; and decoupling techniques for coupled constraint sets that ...
are not readily decomposable. ...
ACKNOWLEDGMENT The authors would like to thank all the collaborators on the subject of decomposition methods and distributed algorithms for network utility maximization, especially, coauthors M. ...
doi:10.1109/jsac.2006.879350
fatcat:yxs5ssvnqngbxpxsolspsnukhq
Fitness-based Linkage Learning in the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm
2020
IEEE Transactions on Evolutionary Computation
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The recently introduced Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm (RV-GOMEA) has been shown to be among the state-of-the-art for solving grey-box optimization problems where partial evaluations ...
a black-box setting where partial evaluations can not be leveraged. 1 ...
Since various real-world optimization problems, as well as all our benchmark problems allow for partial evaluations, we have decided to focus mainly on grey-box optimization in order to obtain a realistic ...
doi:10.1109/tevc.2020.3039698
fatcat:brkd3mempracxb47y7cfugsd3y
Linkage Problem, Distribution Estimation, and Bayesian Networks
2000
Evolutionary Computation
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The proposed algorithm is called the Bayesian Optimization Algorithm (BOA). ...
Except for the maximal order of interactions to be covered, the algorithm does not use any prior knowledge about the problem. ...
Mengshoel for valuable discussions and useful comments. For help with performing a part of the experiments, the authors would also like to thank Pavel Petrovic. ...
doi:10.1162/106365600750078808
pmid:11001554
fatcat:2m23bnimszaolfm6dc62qbp7ei
The Neighbor-Net Algorithm
[article]
2008
arXiv
pre-print
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The algorithm is optimal for Kalmanson matrices, from which it follows that neighbor-net is consistent and has optimal radius 1/2. ...
The neighbor-net algorithm is an extension of the neighbor-joining algorithm and is used for constructing split networks. ...
Equivalently, a partial circular ordering is a partition C of X into ordered sets C = {C 1 , . . . , C m } where each C r ⊆ X and i, j are adjacent elements in C r for some r iff i, j correspond to adjacent ...
arXiv:math/0702515v2
fatcat:lqomqg25wrflzfsvknuqqyqike
Decomposition During Search for Propagation-Based Constraint Solvers
[article]
2008
arXiv
pre-print
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The presented search algorithm dynamically decomposes sub-problems of a constraint satisfaction problem into independent partial problems, avoiding redundant work. ...
We have implemented DDS for the Gecode constraint programming library. ...
Sebastian Will is partially supported by the EU Network of Excellence REWERSE (project number 506779). ...
arXiv:0712.2389v2
fatcat:m5m2z7iu4nepfoi5edkqz3qg2e
Hierarchical problem solving with the linkage tree genetic algorithm
2013
Proceeding of the fifteenth annual conference on Genetic and evolutionary computation conference - GECCO '13
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Results show that, although LTGA is a simple algorithm compared to SEAM and hBOA, it nevertheless is a very efficient, reliable, and scalable algorithm for solving the randomly shuffled versions of HIFF ...
Hierarchical problems represent an important class of nearly decomposable problems. The concept of near decomposability is central to the study of complex systems. ...
A competent hierarchical optimizer must be capable of representing partial solutions at each level compactly to enable the algorithm to effectively process partial solutions of larger order (this becomes ...
doi:10.1145/2463372.2463477
dblp:conf/gecco/ThierensB13
fatcat:cr37g57zqbfnneepjfuzdcxedu
Improved Bagging Algorithm for Pattern Recognition in UHF Signals of Partial Discharges
2011
Energies
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This approach establishes the sample information entropy for each sample and the re-sampling process of the traditional Bagging algorithm is optimized. ...
The optimized third order Peano fractal antenna was applied to capture the PD UHF signals. ...
The fund of National Basic Research Program of China (973 program, 2009CB724508) and the Natural Science Foundation of Chongqing, China (CSTC 2009BA4048) are also appreciated for supporting this work. ...
doi:10.3390/en4071087
fatcat:pnqpkpfokbehzoz5h2wnwfsjwu
Fast Boolean matching based on NPN classification
2013
2013 International Conference on Field-Programmable Technology (FPT)
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This paper proposes a fast algorithm for Boolean matching of completely specified Boolean functions. ...
The algorithm is conceptually simpler, faster, and more scalable than previous work. ...
Profiling the algorithm The functions are partitioned into three sets using disjointsupport decomposition [1] [4] : fully decomposable, partially decomposable, and non-decomposable. ...
doi:10.1109/fpt.2013.6718374
dblp:conf/fpt/HuangWNM13
fatcat:wyzhft3zijd2vozkux3lp6qz24
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