IEEE

A Comparative study of Hyper-Parameter Optimization Tools

Abstract: Most of the machine learning models have associated hyper-parameters along with their parameters. While the algorithm gives the solution for parameters, its utility for model performance is ...
GitHub

Large Language Models for Hyperparameter Optimization

We explore the use of large language models (LLMs) in hyperparameter optimization (HPO). By prompting LLMs with dataset and model descriptions, we develop a methodology where LLMs suggest ...
GitHub

Python Imaging Library (Fork)

Pillow is the friendly PIL fork by Jeffrey A. Clark and contributors. PIL is the Python Imaging Library by Fredrik Lundh and contributors. As of 2019, Pillow development is supported by Tidelift. The ...
Frontiers

Slip detection for compliant robotic hands using inertial signals and deep learning

Collaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University, Corvallis, OR, United States When a passively compliant hand grasps an object, slip events are often ...
IEEE

Competitive Analysis of the Top Gradient Boosting Machine Learning Algorithms

Abstract: In this paper, we compare four state-of-the-art gradient boosting algorithms viz. XGBoost, CatBoost, LightGBM and SnapBoost. All these algorithms are a form of Gradient Boosting Decision ...