Jukka Heikkonen

Stochastic Gradient Optimization with Model-Assisted Sampling

Jonne Pohjankukka, Jukka Heikkonen

This work addresses the problem of variance in stochastic gradient estimation for machine learning optimization. Deep learning relies on mini-batch methods such as stochastic gradient descent, which approximate full gradients but introduce noise, creating trade-offs between conve…Read more