TTESLA: Towards Tera-Scale Nonparametric Learning

Abstract

The project has contributed to the development of optimal and efficient algorithms for large scale machine learning and their applications, with results in three main directions: 1) dealing with data having non Euclidean structure, 2) developing efficient approaches based on random projections, 3)application to the development of efficient AI systems for humanoid robotics. The results of the project have led to new theoretical results, new software and new intelligent systems for robotics. They have been published and presented in the top venues in the field.

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Document Details

Document Type
Technical Report
Publication Date
May 29, 2020
Accession Number
AD1106355

Entities

People

  • Lorenzo Rosasco

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Bayesian Networks
  • Computational Science
  • Computer Languages
  • Computer Vision
  • Data Mining
  • Dimensionality Reduction
  • Geometry
  • Information Processing
  • Information Science
  • Information Systems
  • Kernel Functions
  • Machine Learning
  • Neural Networks
  • Supervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Robotics and Automation.
  • Technical Research and Report Writing.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control