Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
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Updated
Sep 25, 2024 - Python
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
PyTorch Implementation of Attention Prompt Tuning: Parameter-Efficient Adaptation of Pre-Trained Models for Action Recognition
Image augmentation with mixup image tag
Autotuner for Spark applications
Time Series Cross-Validation -- an extension for scikit-learn
Tuning Monte Carlo generators with machine learning.
Package for machine learning of astronomical objects such as light curves
I implement I-AutoRec (an autoencoder framework for collaborative filtering b) with Keras and tuned hyperparameters of this model using a validation set.
Experimental analysis of KNN by using waveform dataset
A multi-thread code for tuning and running several clustering algorithms.
CNVRG platform experimenting with labs package
A novel Sparse-Coding Based Approach Feature Selection with emphasizing joint l_1,2-norm minimization and the Class-Specific Feature Selection.
a library to tune xgboost models
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…
XTune: A custom python wrapper for XGBoost and LightGBM with numerous utility functions to prevent silly gotchas and save time!
HYPO_RFS is an algorithm for performing exhaustive grid-search approach for tuning the hyper-parameters of Ranking Feature Selection (RFS) approaches.
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