MATLAB toolkit for Instance Space Analysis: an automated PRELIM-SIFTED-PILOT-CLOISTER-PYTHIA-TRACE pipeline that projects problem instances into a 2D/3D space and builds algorithm footprints to assess and compare algorithmic power. Powers the MATILDA web platform.

benchmarking optimization matlab genetic-algorithm data-visualization feature-selection classification dimensionality-reduction bayesian-optimization matlab-toolbox algorithm-selection meta-learning research-software matilda algorithm-portfolio instance-space-analysis

• Updated Oct 18, 2026
• MATLAB

Automated Algorithm Selection with Hyperparameter Optimization

algorithm-selection

• Updated Oct 4, 2023
• Python

MachSMT: An ML-Driven Algorithm Selection tool for SMT Solvers

machine-learning smt smt-solver algorithm-selection automated-reasoning

• Updated Aug 28, 2026
• Python

This repo holds the code, dataset, and running scripts for fast k-means evaluation

evaluation pipeline-framework dataset pruning spatial-analysis k-means algorithm-selection lloyds automatic-machine-learning fast-kmeans

• Updated May 20, 2022
• Java

Algorithms to solve and features to characterise TSP problems.

r optimization tsp algorithm-selection traveling-salesperson-problem inexact-tsp-algorithms

• Updated Nov 30, 2021
• R

ASF is a flexible Python library for algorithm selection

python machine-learning algorithm-selection

• Updated Oct 23, 2026
• Python

Sparkle is a Programming by Optimisation (PbO)-based problem-solving platform designed to enable the widespread and effective use of PbO techniques for improving the state-of-the-art in solving a broad range of prominent AI problems, including SAT and AI Planning.

ai algorithm-selection algorithm-configuration

• Updated Sep 8, 2026
• Python

Mosaic: MCTS-based Pipeline Optimization

hyperparameter-optimization algorithm-selection algorithm-configuration

• Updated Jun 26, 2020
• Python

An AutoRecSys Library built around LensKit. Performs automatic algorithm selection, hyperparameter optimzation and ensembling on LensKit models.

hyperparameter-optimization recommender-system bayesian-optimization random-search algorithm-selection automl ensembling smac3 autorecsys

• Updated Jul 3, 2026
• Python

This repository holds the code for our paper "Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis" by Alexander Tornede, Marcel Wever, Stefan Werner, Felix Mohr and Eyke Hüllermeier.

survival-analysis algorithm-selection decision-theory

• Updated May 23, 2023
• Jupyter Notebook

DSH/Codex Agent Skill for CUMCM and mathematical modeling: model selection, algorithm strategy, optimization, and validation.

optimization scientific-computing model-selection chinese operations-research dsh codex algorithm-selection cumcm mathematical-modeling agent-skill deepseek-harness dsh-skill

• Updated Sep 16, 2026

Federated Meta-Learning: a concept that allows everyone to benefit from the data that is generated through machine learning libraries.

machine-learning scikit-learn recommender-system algorithm-selection automl automated-machine-learning meta-learning hyperparameter-search federated-learning federated-meta-learning fmlearn fm-learn algorithm-selection-library

• Updated Sep 30, 2022
• CSS

Uses reinforcement learning to train an algorithm selection model in solving subgraph isomorphism problems.

reinforcement-learning algorithm-selection subgraph-isomorphism dissertation-material

• Updated Dec 17, 2018
• TeX

Automated Algorithm Selection for Time-series Forecasting

algorithm-selection time-series-forecasting

• Updated Apr 8, 2025
• Jupyter Notebook

The idea of this research is based on a novel paradigm for solving complex, NP-hard problems (e.g., schedul- ing, routing) by leveraging Large Language Models (LLMs) as dynamic orchestrators in Agentic solvers, as proposed in a position Paper by professor Roberto Amadini and Simone Gazza.

constraint-programming algorithm-selection minizinc solver-selection

• Updated Sep 11, 2026
• Jupyter Notebook

Papers I've been reading on machine learning (bandits, reinforcement learning, algorithm selection, optimal transport, time series, etc).

machine-learning statistics reinforcement-learning deep-learning time-series optimization recommender-system transfer-learning convex-optimization optimal-transport algorithm-selection bandit

• Updated Mar 10, 2020

Local Streamlit app that suggests and ranks ML, AI, NLP, computer vision, time series, anomaly detection, document intelligence, GenAI, and RAG algorithms for a project.

python nlp data-science machine-learning computer-vision time-series artificial-intelligence openai algorithm-selection anomaly-detection rag mlops streamlit document-intelligence genai

• Updated Aug 16, 2026
• Python

Code and text for the paper "A Comprehensive Study of k-Portfolios of Recent SAT Solvers".

data-science machine-learning sat-solver algorithm-selection

• Updated Oct 4, 2024
• TeX

Short, readable equations predicting the MCC a classifier reaches on a dataset, fitted from meta-features of both by sparse regression over a fixed term library. Validated leave-one-dataset-out and leave-one-model-out; trades accuracy for explainability on purpose.

python reproducible-research symbolic-regression model-selection sparse-regression algorithm-selection interpretability meta-learning explainable-ai matthews-correlation-coefficient

• Updated Nov 3, 2026
• Python

Q-OPS Global: a trusted selective quantum–classical copilot for Human–AI staffing—classical scheduling first, constrained QAOA only on ambiguous feasible cores, and classical certification always. Vanguard/WISER Quantum Challenge 2026.

quantum-computing operations-research algorithm-selection qaoa trustworthy-ai human-ai-collaboration hybrid-quantum-classical workforce-scheduling

• Updated Aug 5, 2026
• Python