2 papers
stat.ML2025
MMbeddings: Parameter-Efficient, Low-Overfitting Probabilistic Embeddings Inspired by Nonlinear Mixed Models
Giora Simchoni, Saharon Rosset
We present MMbeddings, a probabilistic embedding approach that reinterprets categorical embeddings through the lens of nonlinear mixed models, effectively bridging classical statis…
stat.ML2024
Integrating Random Effects in Variational Autoencoders for Dimensionality Reduction of Correlated Data
Giora Simchoni, Saharon Rosset
Variational Autoencoders (VAE) are widely used for dimensionality reduction of large-scale tabular and image datasets, under the assumption of independence between data observation…