Pareto-Based Multiobjective Machine Learning: An Overview and Case Studies
IEEE Transactions on Systems, Man, and Cybernetics, 2008. [All Versions]. A comprehensive review on the application of pareto optimality to multiobjective machine learning.
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Pareto optimality in multiobjective problems link.springer.com
Applied Mathematics and Optimization, 1977. [All Versions]. The original paper on the pareto optimality in multiobjective problems.
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Practical Bayesian Optimization of Machine Learning Algorithms proceedings.neurips.cc
NeurIPS'12, 2012. [All Versions]. The use of machine learning algorithms frequently involves careful tuning of learning parameters and model hyperparameters. Unfortunately, this tuning is often a “black art” requiring expert experience, rules of thumb, or sometimes brute-force…
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A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation proceedings.neurips.cc
NeurIPS'19, 2019. [All Versions].
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Probabilistic machine learning and artificial intelligence nature.com
Nature, 2015. [All Versions]. Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The…
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Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space websites.umich.edu
Science, 2012. [All Versions]. A classic paper correlating biological trade-offs with the evolution of pareto optimality.
AGI & CoCoSci › Papers > Evolutionary Intelligence: “IEEE Transactions on Systems, Man, and Cybernetics, 2008. [All Versions]. A comprehensive review on the application of pareto optimality to multiobjective machine learning.”