1 citations · 2 across the 8 of their papers we have counts for
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Regime Change Hypothesis: Foundations for Decoupled Dynamics in Neural Network Training
Cristian Pérez-Corral, Alberto Fernández-Hernández, Jose I. Mestre +3
Despite the empirical success of DNN, their internal training dynamics remain difficult to characterize. In ReLU-based models, the activation pattern induced by a given input deter…
Why Is Dynamically Special in Adam
Alberto Fernández-Hernández, Cristian Pérez-Corral, Jose I. Mestre +2
Adam has been at the core of large-scale training for almost a decade, yet the role of its two momentum parameters remains poorly understood. Recent work shows that tying $β_{1}=β_…
GLAI: GreenLightningAI for Accelerated Training through Knowledge Decoupling
Jose I. Mestre, Alberto Fernández-Hernández, Cristian Pérez-Corral +3
In this work we introduce GreenLightningAI (GLAI), a new architectural block designed as an alternative to conventional MLPs. The central idea is to separate two types of knowledge…
Sinusoidal Initialization, Time for a New Start
Alberto Fernández-Hernández, Jose I. Mestre, Manuel F. Dolz +2
Initialization plays a critical role in Deep Neural Network training, directly influencing convergence, stability, and generalization. Common approaches such as Glorot and He initi…
OUI Need to Talk About Weight Decay: A New Perspective on Overfitting Detection
Alberto Fernández-Hernández, Jose I. Mestre, Manuel F. Dolz +2
We introduce the Overfitting-Underfitting Indicator (OUI), a novel tool for monitoring the training dynamics of Deep Neural Networks (DNNs) and identifying optimal regularization h…
GreenLightningAI: An Efficient AI System with Decoupled Structural and Quantitative Knowledge
Jose Duato, Jose I. Mestre, Manuel F. Dolz +1
The number and complexity of artificial intelligence (AI) applications is growing relentlessly. As a result, even with the many algorithmic and mathematical advances experienced ov…