Nov 28, 2023 · With this embedding, our DRL algorithm can draw multiple actions from a single state observation and adapt, without retraining, to new ...

With this embedding, our DRL algorithm can draw multiple actions from a single state observation and adapt, without retraining, to new environments unseen in ...

With this embedding, our DRL algorithm can draw multiple actions from a single state observation and adapt, without retraining, to new environments unseen in ...

Duration: 0:46
Posted: Nov 5, 2024

Distributed Computation of DNN via DRL With Spatiotemporal State Embedding. IEEE Internet of Things Journal. 2024-04-01 | Journal article.

Distributed Computation of DNN via DRL With Spatio-Temporal State Embedding. S Kim, S Jung, HW Lee. IEEE Internet of Things Journal, 2023. 2023. Reducing DNN ...

Distributed Computation of DNN via DRL with Spatio-Temporal State Embedding," To appear in IEEE Internet of Things Journal. Sehun Jung and Hyang-Won Lee ...

We develop a deep reinforcement learning (DRL) -based offloading algorithm for computing DNN layers with minimum end-to-end inference latency.

Distributed Computation of DNN via DRL With Spatiotemporal State Embedding · Optimization framework for splitting DNN inference jobs over computing networks.

Sehun Jung, Hyang-Won Lee : Distributed Computation of DNN via DRL With Spatiotemporal State Embedding. IEEE Internet Things J. 11(7): 12686-12701 (2024) ...