A Multi-objective Multi-fidelity acquisition function for Bayesian optimization based on EHVI method.

Paret-Front Diverse Batch Multi-Objective Bayesian Optimization

Preference-Aware Constrained Multi-Objective Bayesian Optimization

Codebase for "AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization", ICML 2018.

Evolution of Heuristics

A model selection framework for learning rate-free reinforcement learning

A framework for QuickTune

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K…

[CVPR 2024] Efficient Hyperparameter Optimization with Adaptive Fidelity Identification

GUI for spotPython

computer vision and sports

Multi-fidelity Gaussian Process Bandit Optimisation

MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information

Robust and conjugate Gaussian process

A system for automating selection and optimization of pre-trained models from the TAO Model Zoo

Reference implementation for "Scalable Meta-Learning with Gaussian Processes" by Tighineanu et al. 2024

Code accompanying https://arxiv.org/abs/1802.02219

Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization

Code for the Population-Based Bandits Algorithm, presented at NeurIPS 2020.

This repository holds the code for our paper "Extreme Algorithm Selection with Dyadic Feature Representation" by Alexander Tornede, Marcel Wever and Eyke Hüllermeier.

[ICML 2024] Official code for the paper "Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark ".