121 citations · 260 across the 20 of their papers we have counts for
5 papers · 1 filter
An Introduction to Probabilistic Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications
Hyeryung Jang, Osvaldo Simeone, Brian Gardner +1
Spiking neural networks (SNNs) are distributed trainable systems whose computing elements, or neurons, are characterized by internal analog dynamics and by digital and sparse synap…
Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence
Nicolas Skatchkovsky, Hyeryung Jang, Osvaldo Simeone
Spiking Neural Networks (SNNs) offer a promising alternative to conventional Artificial Neural Networks (ANNs) for the implementation of on-device low-power online learning and inf…
Solving Continual Combinatorial Selection via Deep Reinforcement Learning
Hyungseok Song, Hyeryung Jang, Hai H. Tran +5
We consider the Markov Decision Process (MDP) of selecting a subset of items at each step, termed the Select-MDP (S-MDP). The large state and action spaces of S-MDPs make them intr…
Learning to Demodulate from Few Pilots via Offline and Online Meta-Learning
Sangwoo Park, Hyeryung Jang, Osvaldo Simeone +1
This paper considers an Internet-of-Things (IoT) scenario in which devices sporadically transmit short packets with few pilot symbols over a fading channel. Devices are characteriz…
Learning How to Demodulate from Few Pilots via Meta-Learning
Sangwoo Park, Hyeryung Jang, Osvaldo Simeone +1
Consider an Internet-of-Things (IoT) scenario in which devices transmit sporadically using short packets with few pilot symbols. Each device transmits over a fading channel and is…