17 citations · 26 across the 8 of their papers we have counts for
3 papers · 1 filter
Feedback Alignment Meets Low-Rank Manifolds: A Structured Recipe for Local Learning
Arani Roy, Marco P. Apolinario, Shristi Das Biswas +1
Training deep neural networks (DNNs) with backpropagation (BP) achieves state-of-the-art accuracy but requires global error propagation and full parameterization, leading to substa…
LANCE: Low Rank Activation Compression for Efficient On-Device Continual Learning
Marco Paul E. Apolinario, Kaushik Roy
On-device learning is essential for personalization, privacy, and long-term adaptation in resource-constrained environments. Achieving this requires efficient learning, both fine-t…
TESS: A Scalable Temporally and Spatially Local Learning Rule for Spiking Neural Networks
Marco Paul E. Apolinario, Kaushik Roy, Charlotte Frenkel
The demand for low-power inference and training of deep neural networks (DNNs) on edge devices has intensified the need for algorithms that are both scalable and energy-efficient.…