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Optimizing Loss Functions Through Multivariate Taylor Polynomial Parameterization
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Optimizing Loss Functions Through Multivariate Taylor Polynomial Parameterization

Santiago Gonzalez
Risto Miikkulainen
ArXiv (abs)PDFHTML

Papers citing "Optimizing Loss Functions Through Multivariate Taylor Polynomial Parameterization"

6 / 6 papers shown
Title
Efficient Activation Function Optimization through Surrogate Modeling
Efficient Activation Function Optimization through Surrogate Modeling
G. Bingham
Risto Miikkulainen
161
4
0
13 Jan 2023
Evolving GAN Formulations for Higher Quality Image Synthesis
Evolving GAN Formulations for Higher Quality Image Synthesis
Santiago Gonzalez
Mohak Kant
Risto Miikkulainen
GAN
80
5
0
17 Feb 2021
Effective Regularization Through Loss-Function Metalearning
Effective Regularization Through Loss-Function MetalearningIEEE Congress on Evolutionary Computation (CEC), 2024
Santiago Gonzalez
Xin Qiu
Risto Miikkulainen
259
0
0
02 Oct 2020
Discovering Parametric Activation Functions
Discovering Parametric Activation Functions
G. Bingham
Risto Miikkulainen
ODL
153
78
0
05 Jun 2020
Meta-learning curiosity algorithms
Meta-learning curiosity algorithms
Ferran Alet
Martin Schneider
Tomas Lozano-Perez
L. Kaelbling
137
65
0
11 Mar 2020
Regularized Evolutionary Population-Based Training
Regularized Evolutionary Population-Based TrainingAnnual Conference on Genetic and Evolutionary Computation (GECCO), 2025
J. Liang
Santiago Gonzalez
Hormoz Shahrzad
Risto Miikkulainen
66
9
0
11 Feb 2020