activity
20182023
most citedGPT in Data Science: A Practical Exploration of Model Selection

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Extending Variability-Aware Model Selection with Bias Detection in Machine Learning Projects

Cristina Tavares, Nathalia Nascimento, Paulo Alencar +1

Data science projects often involve various machine learning (ML) methods that depend on data, code, and models. One of the key activities in these projects is the selection of a m…

cs.AI2023★ 1 cited

GPT in Data Science: A Practical Exploration of Model Selection

Nathalia Nascimento, Cristina Tavares, Paulo Alencar +1

There is an increasing interest in leveraging Large Language Models (LLMs) for managing structured data and enhancing data science processes. Despite the potential benefits, this i…

cs.MA2023★ 1 cited

GPT-in-the-Loop: Adaptive Decision-Making for Multiagent Systems

Nathalia Nascimento, Paulo Alencar, Donald Cowan

This paper introduces the "GPT-in-the-loop" approach, a novel method combining the advanced reasoning capabilities of Large Language Models (LLMs) like Generative Pre-trained Trans…

cs.SE2022★ 1 cited

Agile Assessment Methods: Current State of the Art

Ulisses Telemaco, Paulo Alencar, Donald Cowan +1

Agility Assessment (AA) comprises tools, assessment techniques, and frameworks that focus on indicating how a company or a team is applying agile techniques and eventually pointing…

cs.CY2018

Cluster Lifecycle Analysis: Challenges, Techniques, and Framework

Ivens Portugal, Paulo Alencar, Donald Cowan

Novel forms of data analysis methods have emerged as a significant research direction in the transportation domain. These methods can potentially help to improve our understanding…