10 citations · 11 across the 3 of their papers we have counts for
5 papers
Higher Order Generalization Error for First Order Discretization of Langevin Diffusion
Mufan Bill Li, Maxime Gazeau
We propose a novel approach to analyze generalization error for discretizations of Langevin diffusion, such as the stochastic gradient Langevin dynamics (SGLD). For an toleranc…
An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise
Yeming Wen, Kevin Luk, Maxime Gazeau +3
The choice of batch-size in a stochastic optimization algorithm plays a substantial role for both optimization and generalization. Increasing the batch-size used typically improves…
A general system of differential equations to model first order adaptive algorithms
André Belotto da Silva, Maxime Gazeau
First order optimization algorithms play a major role in large scale machine learning. A new class of methods, called adaptive algorithms, were recently introduced to adjust iterat…
Scalable Recommender Systems through Recursive Evidence Chains
Elias Tragas, Calvin Luo, Maxime Gazeau +2
Recommender systems can be formulated as a matrix completion problem, predicting ratings from user and item parameter vectors. Optimizing these parameters by subsampling data becom…
Implicit Manifold Learning on Generative Adversarial Networks
Kry Yik Chau Lui, Yanshuai Cao, Maxime Gazeau +1
This paper raises an implicit manifold learning perspective in Generative Adversarial Networks (GANs), by studying how the support of the learned distribution, modelled as a subman…