4 papers
Frequency Matching in Spiking Neural Networks for mmWave Sensing
Di Yu, Zhenyu Liao, Changze Lv +7
Millimeter-wave (mmWave) sensing enables privacy-preserving, always-on edge perception, but its measurements are often sparse, temporally irregular, and corrupted by high-frequency…
Generalization in Representation Models via Random Matrix Theory: Application to Recurrent Networks
Yessin Moakher, Malik Tiomoko, Cosme Louart +1
We first study the generalization error of models that use a fixed feature representation (frozen intermediate layers) followed by a trainable readout layer. This setting encompass…
A Random Matrix Perspective of Echo State Networks: From Precise Bias--Variance Characterization to Optimal Regularization
Yessin Moakher, Malik Tiomoko, Cosme Louart +1
We present a rigorous asymptotic analysis of Echo State Networks (ESNs) in a teacher student setting with a linear teacher with oracle weights. Leveraging random matrix theory, we…
ECC-SNN: Cost-Effective Edge-Cloud Collaboration for Spiking Neural Networks
Di Yu, Changze Lv, Xin Du +5
Most edge-cloud collaboration frameworks rely on the substantial computational and storage capabilities of cloud-based artificial neural networks (ANNs). However, this reliance res…