3 citations · 5 across the 22 of their papers we have counts for
7 papers · 1 filter
Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations
Chon-Fai Kam, Xavier Cadet, Miloud Bessafi +1
Neural networks trained on modular arithmetic exhibit grokking, a delayed transition from memorisation to generalisation known to depend on model capacity: too little and the netwo…
RADAR: Relative Angular Divergence Across Representations
Xavier Cadet, Mateusz Nowak, Peter Chin
Machine learning methods rely on data. However, gathering suitable data can be challenging due to availability constraints, cost, or the need for domain expertise. Expanding datase…
WARP: Weight Teleportation for Attack-Resilient Unlearning Protocols
Mohammad M Maheri, Xavier Cadet, Peter Chin +1
Approximate machine unlearning aims to efficiently remove the influence of specific data points from a trained model, offering a practical alternative to full retraining. However,…
PoolFlip: A Multi-Agent Reinforcement Learning Security Environment for Cyber Defense
Xavier Cadet, Simona Boboila, Sie Hendrata Dharmawan +2
Cyber defense requires automating defensive decision-making under stealthy, deceptive, and continuously evolving adversarial strategies. The FlipIt game provides a foundational fra…
Deep Unlearn: Benchmarking Machine Unlearning for Image Classification
Xavier F. Cadet, Anastasia Borovykh, Mohammad Malekzadeh +2
Machine unlearning (MU) aims to remove the influence of particular data points from the learnable parameters of a trained machine learning model. This is a crucial capability in li…
Low-Energy On-Device Personalization for MCUs
Yushan Huang, Ranya Aloufi, Xavier Cadet +3
Microcontroller Units (MCUs) are ideal platforms for edge applications due to their low cost and energy consumption, and are widely used in various applications, including personal…