AttributionScanner: A Visual Analytics System for Metadata-Free Data-Slicing Based Model Validation

no code implementations • 12 Jan 2024 • Xiwei Xuan, Jorge Piazentin Ono, Liang Gou, Kwan-Liu Ma, Liu Ren

Data slice-finding is an emerging technique for evaluating machine learning models.

AlphaD3M: Machine Learning Pipeline Synthesis

no code implementations • 3 Nov 2021 • Iddo Drori, Yamuna Krishnamurthy, Remi Rampin, Raoni de Paula Lourenco, Jorge Piazentin Ono, Kyunghyun Cho, Claudio Silva, Juliana Freire

We introduce AlphaD3M, an automatic machine learning (AutoML) system based on meta reinforcement learning using sequence models with self play.

AutoML BIG-bench Machine Learning +3

PipelineProfiler: A Visual Analytics Tool for the Exploration of AutoML Pipelines

1 code implementation • arXiv 2020 • Jorge Piazentin Ono, Sonia Castelo, Roque Lopez, Enrico Bertini, Juliana Freire, Claudio Silva

In recent years, a wide variety of automated machine learning (AutoML) methods have been proposed to search and generate end-to-end learning pipelines.

Human-Computer Interaction

Visus: An Interactive System for Automatic Machine Learning Model Building and Curation

no code implementations • 5 Jul 2019 • Aécio Santos, Sonia Castelo, Cristian Felix, Jorge Piazentin Ono, Bowen Yu, Sungsoo Hong, Cláudio T. Silva, Enrico Bertini, Juliana Freire

In this paper, we present Visus, a system designed to support the model building process and curation of ML data processing pipelines generated by AutoML systems.

AutoML BIG-bench Machine Learning