Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
- Updated
May 7, 2025 - Python
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Time Series Cross-Validation -- an extension for scikit-learn
A novel Sparse-Coding Based Approach Feature Selection with emphasizing joint l_1,2-norm minimization and the Class-Specific Feature Selection.
Package for machine learning of astronomical objects such as light curves
PyTorch Implementation of Attention Prompt Tuning: Parameter-Efficient Adaptation of Pre-Trained Models for Action Recognition
Swarming behaviour is based on aggregation of simple drones exhibiting basic instinctive reactions to stimuli. However, to achieve overall balanced/interesting behaviour the relative importance of these instincts, as well their internal parameters, must be tuned. In this project, you will learn how to apply Genetic Programming as means of such t…
a library to tune xgboost models
Autotuner for Spark applications
Tuning Monte Carlo generators with machine learning.
XTune: A custom python wrapper for XGBoost and LightGBM with numerous utility functions to prevent silly gotchas and save time!
Attrition Models (Hyperparameter Tuning) for Credit Card Attrition (World Bank Credit Union)
Experimental analysis of KNN by using waveform dataset
A multi-thread code for tuning and running several clustering algorithms.
I implement I-AutoRec (an autoencoder framework for collaborative filtering b) with Keras and tuned hyperparameters of this model using a validation set.
A tool for automatic tuning of OpenMP thread team size
PID control interface for Windows and Linux using Python. The application communicates with an Arduino device via a serial connection, displaying sensor readings and allowing users to adjust PID control parameters dynamically. Can be used with any microcontroller through Serial over USB.
CNVRG platform experimenting with labs package
HYPO_RFS is an algorithm for performing exhaustive grid-search approach for tuning the hyper-parameters of Ranking Feature Selection (RFS) approaches.
Image augmentation with mixup image tag
Add a description, image, and links to the tuning-parameters topic page so that developers can more easily learn about it.
To associate your repository with the tuning-parameters topic, visit your repo's landing page and select "manage topics."