InfoWorld

The ‘toggle-away’ efficiencies: Cutting AI costs inside the training loop

You don't need the newest GPUs to save money on AI; simple tweaks like "smoke tests" and fixing data bottlenecks can slash ...
GitHub

4_train_policy_with_script.md

Initialize/load a configuration for the following steps using. Instantiates a dataset. (Optional) Instantiates a simulation environment corresponding to that dataset. Instantiates a policy. Runs a ...
GitHub

README_Qwen_Smolvlm.md

Below are the instructions for using the LLM-Pruner method to perform structured pruning and LoRA finetuning on Qwen2.5-3B and SmolVLM-500M-Instruct models. python ...
IEEE

HALO: Hyperparameter Auto-tuning via LLM Optimizer for Rapid, Interpretable AutoML

Abstract: The efficacy of machine learning across scientific and industrial domains hinges critically on hyperparameter configuration, a process that dominates model performance yet remains ...
IEEE

Hyperparameter Tuning and Its Application in Sentiment Analysis with Convolutional Neural Network

Abstract: In this paper, we explore hyperparameter tuning methods for a convolutional neural network (CNN) applied to sentiment analysis on the IMDB movie reviews dataset. Four popular hyperparameter ...