Snowcat and CAVA: Visualization Tools for Interacting with AutoML and Knowledgebases

Abstract

The goal of our project is to create visualization systems that enable subject matter experts (SMEs) to construct, curate, evaluate, and assess data-centric machine learning models. Our systems allow a SME to explore data visually, construct objective functions via intuitive interfaces, and submit them to an AutoML system to generate machine learning models. By integrating visual exploration of input data, model outputs, and visualization results, our systems supports model development, tuning, formalization, validation in an intuitive manner decoupled from the underlying modeling techniques.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2021
Accession Number
AD1147924

Entities

People

  • Remco Chang

Organizations

  • Tufts University

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computer Graphics
  • Computer Programming
  • Computers
  • Convolutional Neural Networks
  • Data Analysis
  • Data Sets
  • Engineering
  • Graphics
  • Information Science
  • Information Systems
  • Literature Surveys
  • Machine Learning
  • Neural Networks
  • United States
  • Visualizations

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Database Systems and Applications
  • Distributed Systems and Data Platform Development

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks