A new 5G radio evolution towards 5G-Advanced
The evolution of the fifth-generation (5G) new radio (NR) has progressed swiftly since the
third generation partnership project (3GPP) standardized the first NR version (Release 15) …
third generation partnership project (3GPP) standardized the first NR version (Release 15) …
Energy-aware task scheduling and offloading using deep reinforcement learning in SDN-enabled IoT network
Abstract The fifth-generation (5G) mobile network services have made tremendous growth in
the Internet of Things (IoT) network. A counters number of battery-powered IoT devices are …
the Internet of Things (IoT) network. A counters number of battery-powered IoT devices are …
Neurovectorizer: End-to-end vectorization with deep reinforcement learning
One of the key challenges arising when compilers vectorize loops for today's SIMD-
compatible architectures is to decide if vectorization or interleaving is beneficial. Then, the …
compatible architectures is to decide if vectorization or interleaving is beneficial. Then, the …
Genet: automatic curriculum generation for learning adaptation in networking
As deep reinforcement learning (RL) showcases its strengths in networking, its pitfalls are
also coming to the public's attention. Training on a wide range of network environments …
also coming to the public's attention. Training on a wide range of network environments …
A survey on deep reinforcement learning for data processing and analytics
Data processing and analytics are fundamental and pervasive. Algorithms play a vital role in
data processing and analytics where many algorithm designs have incorporated heuristics …
data processing and analytics where many algorithm designs have incorporated heuristics …
Two-stage WECC composite load modeling: A double deep Q-learning networks approach
With the increasing complexity of modern power system, conventional dynamic load
modeling with ZIP and induction motors (ZIP+ IM) is no longer adequate to address the …
modeling with ZIP and induction motors (ZIP+ IM) is no longer adequate to address the …
Byzantine-fault-tolerant consensus via reinforcement learning for permissioned blockchain-empowered V2X network
S Kim, AS Ibrahim - IEEE Transactions on Intelligent Vehicles, 2022 - ieeexplore.ieee.org
Blockchain has been forming the central piece of various types of vehicle-to-everything
(V2X) network for trusted data exchange. Recently, permissioned blockchains garner …
(V2X) network for trusted data exchange. Recently, permissioned blockchains garner …
A hybrid reinforcement learning-based model for the vehicle routing problem in transportation logistics
T Phiboonbanakit, T Horanont, VN Huynh… - IEEE …, 2021 - ieeexplore.ieee.org
Currently, the number of deliveries handled by transportation logistics is rapidly increasing
because of the significant growth of the e-commerce industry, resulting in the need for …
because of the significant growth of the e-commerce industry, resulting in the need for …
InTune: Reinforcement learning-based data pipeline optimization for deep recommendation models
K Nagrecha, L Liu, P Delgado… - Proceedings of the 17th …, 2023 - dl.acm.org
Deep learning-based recommender models (DLRMs) have become an essential component
of many modern recommender systems. Several companies are now building large compute …
of many modern recommender systems. Several companies are now building large compute …
When architecture meets AI: A deep reinforcement learning approach for system of systems design
How to design System of Systems has been widely concerned in recent years, especially in
military applications. This problem is also known as SoS architecting, which can be boiled …
military applications. This problem is also known as SoS architecting, which can be boiled …