Sequential model-based optimization with a `scipy.optimize` interface
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Updated
Feb 23, 2024 - Python
Sequential model-based optimization with a `scipy.optimize` interface
Automatically create a config of hyper-parameters from global variables
Hyper-Parameter Analyzer
A small library for managing deep learning models, hyperparameters and datasets
A dl management front end
Tools for Optuna, MLflow and the integration of both.
Hyper-parameter tuner (for computer vision and reinforcement learning)
Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"
Example Code for paper "Provably Faster Algorithms for Bilevel Optimization"
Interactive exploration of hyperparameter tuning results with ipywidget and plotly in jupyter notebook.
A simple python interface for running multiple parallel instances of a python program (e.g. gridsearch).
Hyperparameter optimisation utility for lightgbm and xgboost using hyperopt.
PyTorch implementation of Proximal Gradient Algorithms a la Parikh and Boyd (2014). Useful for Auto-Sizing (Murray and Chiang 2015, Murray et al. 2019).
Distributed Asynchronous Hyperparameter Optimization in Python
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