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Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.

copied from cf-staging / r-dfoptim
Type Size Name Uploaded Downloads Labels
conda 90.1 kB | noarch/r-dfoptim-2020.10_1-r43hc72bb7e_2.conda  1 year and 5 months ago 878 main
conda 90.6 kB | noarch/r-dfoptim-2020.10_1-r42hc72bb7e_2.conda  1 year and 5 months ago 1066 main
conda 91.7 kB | noarch/r-dfoptim-2020.10_1-r42hc72bb7e_1.tar.bz2  2 years and 2 months ago 1272 main
conda 91.7 kB | noarch/r-dfoptim-2020.10_1-r41hc72bb7e_1.tar.bz2  2 years and 2 months ago 1312 main
conda 90.7 kB | noarch/r-dfoptim-2020.10_1-r40hc72bb7e_0.tar.bz2  3 years and 6 months ago 1929 main
conda 90.7 kB | noarch/r-dfoptim-2020.10_1-r41hc72bb7e_0.tar.bz2  3 years and 6 months ago 1923 main
conda 90.5 kB | noarch/r-dfoptim-2020.10_1-r40h142f84f_0.tar.bz2  4 years and 1 month ago 2300 main
conda 91.3 kB | noarch/r-dfoptim-2020.10_1-r36h142f84f_0.tar.bz2  4 years and 1 month ago 2327 main

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