Cooperate or not Cooperate: Transfer Learning with Multi-Armed Bandit for Spatial Reuse in Wi-Fi
PE Iturria-Rivera, M Chenier… - … Machine Learning in …, 2024 - ieeexplore.ieee.org
The exponential increase in the demand for high-performance services such as streaming
video and gaming by wireless devices has posed several challenges for Wireless Local …
video and gaming by wireless devices has posed several challenges for Wireless Local …
Two-Stage Neural Contextual Bandits for Personalised News Recommendation
We consider the problem of personalised news recommendation where each user
consumes news in a sequential fashion. Existing personalised news recommendation …
consumes news in a sequential fashion. Existing personalised news recommendation …
Improving Reward-Conditioned Policies for Multi-Armed Bandits using Normalized Weight Functions
K Xu, F Tajaddodianfar, B Allison - arXiv preprint arXiv:2406.10795, 2024 - arxiv.org
Recently proposed reward-conditioned policies (RCPs) offer an appealing alternative in
reinforcement learning. Compared with policy gradient methods, policy learning in RCPs is …
reinforcement learning. Compared with policy gradient methods, policy learning in RCPs is …
MC Layer Normalization for calibrated uncertainty in Deep Learning
Efficiently estimating the uncertainty of neural network predictions has become an
increasingly important challenge as machine learning models are adopted for high-stakes …
increasingly important challenge as machine learning models are adopted for high-stakes …
UCB Exploration for Fixed-Budget Bayesian Best Arm Identification
RJB Zhu, Y Qiu - arXiv preprint arXiv:2408.04869, 2024 - arxiv.org
We study best-arm identification (BAI) in the fixed-budget setting. Adaptive allocations based
on upper confidence bounds (UCBs), such as UCBE, are known to work well in BAI …
on upper confidence bounds (UCBs), such as UCBE, are known to work well in BAI …
Meta-Bandit: Spatial Reuse Adaptation via Meta-Learning in Distributed Wi-Fi 802.11 ax
PE Iturria-Rivera, M Chenier, B Herscovici… - IEEE Networking …, 2023 - ieeexplore.ieee.org
IEEE 802.11 ax introduces several amendments to previous standards with a special
interest in spatial reuse (SR) to respond to dense user scenarios with high demanding …
interest in spatial reuse (SR) to respond to dense user scenarios with high demanding …
Reinforcement learning for bandits with continuous actions and large context spaces
We consider the challenging scenario of contextual bandits with continuous actions and
large context spaces. This is an increasingly important application area in personalised …
large context spaces. This is an increasingly important application area in personalised …
$\sbf {\delta^ 2} $-exploration for Reinforcement Learning
Effectively tackling the\emph {exploration-exploitation dilemma} is still a major challenge in
reinforcement learning. Uncertainty-based exploration strategies developed in the bandit …
reinforcement learning. Uncertainty-based exploration strategies developed in the bandit …