2 citations · 3 across the 5 of their papers we have counts for
5 papers
The Energy Consumption of Transformer Fine-Tuning: A Roofline-Inspired Scaling Model
Mansour Zoubeirou a Mayaki
Transformer-based models underpin modern natural language processing but incur rapidly growing computational and energy costs. As training scales in both model size and parallelism…
Generalization and Scaling Laws for Mixture-of-Experts Transformers
Mansour Zoubeirou a Mayaki
We develop a theory of generalization and scaling for Mixture-of-Experts (MoE) Transformers that cleanly separates \emph{active} per-input capacity from routing combinatorics. By c…
AnoRand: A Semi Supervised Deep Learning Anomaly Detection Method by Random Labeling
Mansour Zoubeirou A Mayaki, Michel Riveill
Anomaly detection or more generally outliers detection is one of the most popular and challenging subject in theoretical and applied machine learning. The main challenge is that in…
Multiple Inputs Neural Networks for Medicare fraud Detection
Mansour Zoubeirou A Mayaki, Michel Riveill
Medicare fraud results in considerable losses for governments and insurance companies and results in higher premiums from clients. Medicare fraud costs around 13 billion euros in E…
Autoregressive based Drift Detection Method
Mansour Zoubeirou A Mayaki, Michel Riveill
In the classic machine learning framework, models are trained on historical data and used to predict future values. It is assumed that the data distribution does not change over ti…