Results 11 to 20 of about 14,697 (286)

Random Pareto front surfaces

CoRR
The code is available at: https://github.com/benmltu ...
Ben Tu, Nikolas Kantas, Robert M. Lee, Behrang Shafei   +3 more
openaire   +3 more sources

Finding Pareto-front Membership Functions in Fuzzy Data Mining [PDF]

International Journal of Computational Intelligence Systems, 2012
Transactions with quantitative values are commonly seen in real-world applications. Fuzzy mining algorithms have thus been developed recently to induce linguistic knowledge from quantitative databases.
Chun-Hao Chen, Tzung-Pei Hong, VincentS. Tseng   +2 more
doaj   +2 more sources

Version [2.0] — [pyMCMA: Uniformly distributed Pareto-front representation] [PDF]

SoftwareX
pyMCMA is the Python implementation of a novel method for autonomous computation of the Pareto-front representation composed of efficient solutions distributed uniformly in terms of the distances between neighbor Pareto solutions.
Marek Makowski, Janusz Granat, Andrii Shekhovtsov, Zbigniew Nahorski, Jinyang Zhao   +4 more
doaj   +2 more sources

Constructing a Pareto front approximation for decision making [PDF]

Mathematical Methods of Operations Research, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Markus Hartikainen, Kaisa Miettinen, Margaret M. Wiecek   +2 more
core   +7 more sources

Trade-off between conservation of biological variation and batch effect removal in deep generative modeling for single-cell transcriptomics

BMC Bioinformatics, 2022
Background Single-cell RNA sequencing (scRNA-seq) technology has contributed significantly to diverse research areas in biology, from cancer to development.
Hui Li, Davis J. McCarthy, Heejung Shim, Susan Wei   +3 more
doaj   +1 more source

Penyelesaian Masalah Optimisasi Multiobjektif Nonlinear Menggunakan Pendekatan Pareto Front dalam Metode Pembobotan

Jurnal Matematika Integratif, 2020
Teori optimisai merupakan salah satu disiplin ilmu matematika yang banyak diterapkan dalam dunia nyata. Hampir semua masalah optimisasi di dunia nyata memiliki banyak fungsi objektif (multiobjektive) yang harus dipenuhi secara simultan dan seringkali ...
Syarifah Inayati, Rahmawati Rahmawati
doaj   +1 more source

Preprocessing Imprecise Points for the Pareto Front [PDF]

, 2022
In the preprocessing model for uncertain data we are given a set of regions R which model the uncertainty associated with an unknown set of points P. In this model there are two phases: a preprocessing phase, in which we have access only to R, followed by a reconstruction phase, in which we have access to points in P at a certain retrieval cost C per ...
Ivor van der Hoog, Irina Kostitsyna, Maarten Löffler, Bettina Speckmann   +3 more
openaire   +3 more sources

Learning the Pareto Front with Hypernetworks

CoRR, 2020
Accepted to ICLR ...
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik   +3 more
openaire   +3 more sources

Efficient Elitist Cooperative Evolutionary Algorithm for Multi-Objective Reinforcement Learning

IEEE Access, 2023
Sequential decision-making problems with multiple objectives are known as multi-objective reinforcement learning. In these scenarios, decision-makers require a complete Pareto front that consists of Pareto optimal solutions. Such a front enables decision-
Dan Zhou, Jiqing Du, Sachiyo Arai
doaj   +1 more source

Automatic Discovery of Privacy–Utility Pareto Fronts [PDF]

Proceedings on Privacy Enhancing Technologies, 2020
Abstract Differential privacy is a mathematical framework for privacy-preserving data analysis. Changing the hyperparameters of a differentially private algorithm allows one to trade off privacy and utility in a principled way. Quantifying this trade-off in advance is essential to decision-makers tasked with deciding how much privacy can
Brendan Avent, Javier González 0002, Tom Diethe, Andrei Paleyes, Borja Balle   +4 more
openaire   +2 more sources