4 papers
Understanding Adam Requires Better Rotation Dependent Assumptions
Tianyue H. Zhang, Lucas Maes, Alan Milligan +5
Despite its widespread adoption, Adam's advantage over Stochastic Gradient Descent (SGD) lacks a comprehensive theoretical explanation. This paper investigates Adam's sensitivity t…
Generating Tabular Data Using Heterogeneous Sequential Feature Forest Flow Matching
Ange-Clément Akazan, Alexia Jolicoeur-Martineau, Ioannis Mitliagkas
Privacy and regulatory constraints make data generation vital to advancing machine learning without relying on real-world datasets. A leading approach for tabular data generation i…
PopulAtion Parameter Averaging (PAPA)
Alexia Jolicoeur-Martineau, Emy Gervais, Kilian Fatras +2
Ensemble methods combine the predictions of multiple models to improve performance, but they require significantly higher computation costs at inference time. To avoid these costs,…
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
Alexia Jolicoeur-Martineau, Kilian Fatras, Tal Kachman
Tabular data is hard to acquire and is subject to missing values. This paper introduces a novel approach for generating and imputing mixed-type (continuous and categorical) tabular…