| BatchGradFun typedef | cpu_mlp::StochasticGradientDescent< V, M > | |
| recorder_ | cpu_mlp::StochasticMinimizer< V, M > | protected |
| S_VecFun typedef | cpu_mlp::StochasticGradientDescent< V, M > | |
| sample_minibatch_indices(const size_t N, size_t batch_size, std::mt19937 &rng) | cpu_mlp::StochasticGradientDescent< V, M > | static |
| setData(const M &inputs, const M &targets, const S_VecFun &f, const BatchGradFun &g) | cpu_mlp::StochasticGradientDescent< V, M > | inline |
| setMaxIterations(int max_iters) | cpu_mlp::StochasticGradientDescent< V, M > | inline |
| cpu_mlp::StochasticMinimizer::setMaxIterations(int max_iters) | cpu_mlp::StochasticMinimizer< V, M > | inline |
| setRecorder(::IterationRecorder< CpuBackend > *recorder) | cpu_mlp::StochasticMinimizer< V, M > | inline |
| setStepSize(double s) | cpu_mlp::StochasticGradientDescent< V, M > | inline |
| cpu_mlp::StochasticMinimizer::setStepSize(double s) | cpu_mlp::StochasticMinimizer< V, M > | inline |
| setTolerance(double tol) | cpu_mlp::StochasticGradientDescent< V, M > | inline |
| cpu_mlp::StochasticMinimizer::setTolerance(double tol) | cpu_mlp::StochasticMinimizer< V, M > | inline |
| stochastic_solve(const V &init_w, int m, int b, double step, bool verbose=false, int print_every=50) | cpu_mlp::StochasticGradientDescent< V, M > | inline |
| StochasticGradientDescent()=default | cpu_mlp::StochasticGradientDescent< V, M > | |
| ~StochasticMinimizer()=default | cpu_mlp::StochasticMinimizer< V, M > | virtual |
