4 papers
Phase-HDC: Replacing Optimizer History with Gradient Thresholds in Discrete Phase Learning
Ahmed Nebli
Training a compact model often needs far more memory than storing it, because the optimizer keeps its own records of past gradients. For a hyperdimensional classifier whose learned…
The Quantum Shortcut: Complex Phase-State Dynamics Reduce the Optimization Steps of Sequence Models
Ahmed Nebli, Hadi Saadatdoorabi, Christopher Keibel +1
Sequence models are conventionally distinguished by their backbone, the mechanism that routes information across positions, such as attention or recurrence. This paper varies a cho…
Deep Sequence Modeling with Quantum Dynamics: Language as a Wave Function
Ahmed Nebli, Hadi Saadatdoorabi, Kevin Yam
We introduce a sequence modeling framework in which the latent state is a complex-valued wave function evolving on a finite-dimensional Hilbert space under a learned, time-dependen…
Unifying Sign and Magnitude for Optimizing Deep Vision Networks via ThermoLion
Ahmed Nebli
The training of deep vision models is fundamentally a signal recovery problem amidst high-dimensional stochastic noise. Current optimization paradigms impose a static compromise on…