On Stability and Concentration of Measure

Abstract

Stability conditions can be thought of as a way of controlling the variance of the learning process. Strong stability conditions additionally imply concentration of certain quantities around their expected values. It was shown recently that stability of learning algorithms is closely related to their generalization and consistency. In this paper we examine stability conditions from this point of view.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2004
Accession Number
ADA459829

Entities

People

  • Alexander Rakhlin
  • Sayan Mukherjee
  • Tomaso Poggio

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Artificial Intelligence
  • Computations
  • Computer Science
  • Consistency
  • Contracts
  • Convergence
  • Electric Power
  • Inequalities
  • Information Operations
  • Learning
  • Military Research
  • Probability
  • Random Variables
  • Stability Conditions
  • Symmetry

Readers

  • Computational Modeling and Simulation
  • Fluid Dynamics.
  • Organizational Process Management (OPM).