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Pareto-optimal Community Search on Large Bipartite Graphs
International Conference on Information and Knowledge Management, 2021In many real-world applications, bipartite graphs are naturally used to model relationships between two types of entities. Community discovery over bipartite graphs is a fundamental problem and has attracted much attention recently. However, all existing
Yuting Zhang +4 more
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IEEE Computational Intelligence Magazine, 2020
To represent a many-objective Pareto-optimal front having four or more dimensions of the objective space, a large number of points are necessary. However, for choosing a single preferred point from a large set is problematic and time-consuming, as they ...
A. K. Talukder, K. Deb
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To represent a many-objective Pareto-optimal front having four or more dimensions of the objective space, a large number of points are necessary. However, for choosing a single preferred point from a large set is problematic and time-consuming, as they ...
A. K. Talukder, K. Deb
semanticscholar +1 more source
DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures
European Conference on Computer Vision, 2018Recent breakthroughs in Neural Architectural Search (NAS) have achieved state-of-the-art performances in applications such as image classification and language modeling.
Jin-Dong Dong +4 more
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Age-Fitness Pareto Optimization
Proceedings of the 12th annual conference on Genetic and evolutionary computation, 2010We propose a multi-objective method for avoiding premature convergence in evolutionary algorithms, and demonstrate a three-fold performance improvement over comparable methods. Previous research has shown that partitioning an evolving population into age groups can greatly improve the ability to identify global optima and avoid converging to local ...
Michael D. Schmidt, Hod Lipson
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Searching for Local Pareto Optimal Solutions: A Case Study on Polygon-Based Problems
IEEE Congress on Evolutionary Computation, 2019Local Pareto optimal solutions may exist in multi-modal multi-objective optimization problems. Traditional multi-objective evolutionary algorithms usually try to escape from local Pareto optima.
Yiping Liu +4 more
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Progressive Approaches for Pareto Optimal Groups Computation
IEEE Transactions on Knowledge and Data Engineering, 2019Group skyline query is a powerful tool for optimal group analysis. Most of the existing group skyline queries select optimal groups by comparing the dominance relationship between aggregate-based points; such feature creates difficulties for users to ...
Xu Zhou +4 more
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Pareto Optimal Pairwise Sequence Alignment
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2013Sequence alignment using evolutionary profiles is a commonly employed tool when investigating a protein. Many profile-profile scoring functions have been developed for use in such alignments, but there has not yet been a comprehensive study of Pareto optimal pairwise alignments for combining multiple such functions.
Kevin W, DeRonne, George, Karypis
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Finding Pareto Optimal Groups: Group-based Skyline
Proceedings of the VLDB Endowment, 2015Skyline computation, aiming at identifying a set of skyline points that are not dominated by any other point, is particularly useful for multi-criteria data analysis and decision making. Traditional skyline computation, however, is inadequate to answer
Jinfei Liu +4 more
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2003
Abstract In Parts 1 and 2 we showed that with differentiable preferences, Pareto optimality implies a unique Arrow-Debreu, or Martingale, measure. In this chapter we show that the extension to multiple commodities leaves the proofs largely unchanged.
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Abstract In Parts 1 and 2 we showed that with differentiable preferences, Pareto optimality implies a unique Arrow-Debreu, or Martingale, measure. In this chapter we show that the extension to multiple commodities leaves the proofs largely unchanged.
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2019
The decision making problems mostly involve optimization of multiple conflicting objectives. The investigation of trade-off between the objectives under a prescribed set of constraints generates a bunch of Pareto-optimal solutions. In this chapter the multiobjective optimization problem is studied in fuzzy environment. The concept of efficient solution
Debdas Ghosh, Debjani Chakraborty
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The decision making problems mostly involve optimization of multiple conflicting objectives. The investigation of trade-off between the objectives under a prescribed set of constraints generates a bunch of Pareto-optimal solutions. In this chapter the multiobjective optimization problem is studied in fuzzy environment. The concept of efficient solution
Debdas Ghosh, Debjani Chakraborty
openaire +1 more source