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ALGORITHME GRADIENT STOCHASTIQUE [1 record]

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Record 1 2024-01-10

English

Subject field(s)
  • Computer Mathematics
  • Computer Programs and Programming
  • Artificial Intelligence
CONT

Stochastic gradient algorithms are widely used for large-scale learning and inference problems. However, their use in practice is typically guided by heuristics and trial-and-error rather than rigorous, generalizable theory.

CONT

Stochastic gradient descent (SGD) and its variants have established themselves as the go-to algorithms for large-scale machine learning problems with independent samples due to their generalization performance and intrinsic computational advantage.

French

Domaine(s)
  • Mathématiques informatiques
  • Programmes et programmation (Informatique)
  • Intelligence artificielle

Spanish

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