7 citations · 11 across the 21 of their papers we have counts for
14 papers · 1 filter
Adaptive Head Budgeting for Efficient Multi-Head Attention
Bilal Faye, Abdoulaye Mbaye, Hanane Azzag +1
Multi-head attention enables Transformers to capture diverse representations, but all attention heads are typically activated for every input, regardless of task complexity. For co…
Prototype-Guided Diffusion: Visual Conditioning without External Memory
Bilal Faye, Hanane Azzag, Mustapha Lebbah
Diffusion models achieve state-of-the-art image generation but remain computationally costly due to iterative denoising. Latent-space models like Stable Diffusion reduce overhead y…
Value-Free Policy Optimization via Reward Partitioning
Bilal Faye, Hanane Azzag, Mustapha Lebbah
Single-trajectory preference optimization methods learn from datasets of ((prompt, response, reward)) tuples, offering a practical alternative to pairwise preference learning by di…
Game Theory Meets Statistical Mechanics in Deep Learning Design
Djamel Bouchaffra, Fayçal Ykhlef, Bilal Faye +2
We present a novel deep graphical representation that seamlessly merges principles of game theory with laws of statistical mechanics. It performs feature extraction, dimensionality…
Evaluating the Efficacy of Instance Incremental vs. Batch Learning in Delayed Label Environments: An Empirical Study on Tabular Data Streaming for Fraud Detection
Kodjo Mawuena Amekoe, Mustapha Lebbah, Gregoire Jaffre +2
Real-world tabular learning production scenarios typically involve evolving data streams, where data arrives continuously and its distribution may change over time. In such a setti…
Unsupervised Adaptive Normalization
Bilal Faye, Hanane Azzag, Mustapha Lebbah +1
Deep neural networks have become a staple in solving intricate problems, proving their mettle in a wide array of applications. However, their training process is often hampered by…