Reinforcement learning based recommender systems: A survey

MM Afsar, T Crump, B Far - ACM Computing Surveys, 2022 - dl.acm.org
Recommender systems (RSs) have become an inseparable part of our everyday lives. They
help us find our favorite items to purchase, our friends on social networks, and our favorite …

Machine learning for reliability engineering and safety applications: Review of current status and future opportunities

Z Xu, JH Saleh - Reliability Engineering & System Safety, 2021 - Elsevier
Abstract Machine learning (ML) pervades an increasing number of academic disciplines and
industries. Its impact is profound, and several fields have been fundamentally altered by it …

Bias and debias in recommender system: A survey and future directions

J Chen, H Dong, X Wang, F Feng, M Wang… - ACM Transactions on …, 2023 - dl.acm.org
While recent years have witnessed a rapid growth of research papers on recommender
system (RS), most of the papers focus on inventing machine learning models to better fit …

[HTML][HTML] A survey on Zero touch network and Service Management (ZSM) for 5G and beyond networks

M Liyanage, QV Pham, K Dev, S Bhattacharya… - Journal of Network and …, 2022 - Elsevier
Faced with the rapid increase in smart Internet-of-Things (IoT) devices and the high demand
for new business-oriented services in the fifth-generation (5G) and beyond network, the …

Reinforcement learning to optimize long-term user engagement in recommender systems

L Zou, L **a, Z Ding, J Song, W Liu, D Yin - Proceedings of the 25th ACM …, 2019 - dl.acm.org
Recommender systems play a crucial role in our daily lives. Feed streaming mechanism has
been widely used in the recommender system, especially on the mobile Apps. The feed …

Multi-armed bandits in recommendation systems: A survey of the state-of-the-art and future directions

N Silva, H Werneck, T Silva, ACM Pereira… - Expert Systems with …, 2022 - Elsevier
Abstract Recommender Systems (RSs) have assumed a crucial role in several digital
companies by directly affecting their key performance indicators. Nowadays, in this era of big …

KuaiSim: A comprehensive simulator for recommender systems

K Zhao, S Liu, Q Cai, X Zhao, Z Liu… - Advances in …, 2023 - proceedings.neurips.cc
Reinforcement Learning (RL)-based recommender systems (RSs) have garnered
considerable attention due to their ability to learn optimal recommendation policies and …

Off-policy actor-critic for recommender systems

M Chen, C Xu, V Gatto, D Jain, A Kumar… - Proceedings of the 16th …, 2022 - dl.acm.org
Industrial recommendation platforms are increasingly concerned with how to make
recommendations that cause users to enjoy their long term experience on the platform …

Linrec: Linear attention mechanism for long-term sequential recommender systems

L Liu, L Cai, C Zhang, X Zhao, J Gao, W Wang… - Proceedings of the 46th …, 2023 - dl.acm.org
Transformer models have achieved remarkable success in sequential recommender
systems (SRSs). However, computing the attention matrix in traditional dot-product attention …

[HTML][HTML] A survey of deep reinforcement learning application in 5G and beyond network slicing and virtualization

C Ssengonzi, OP Kogeda, TO Olwal - Array, 2022 - Elsevier
Abstract The 5th Generation (5G) and beyond networks are expected to offer huge
throughputs, connect large number of devices, support low latency and large numbers of …