Results 51 to 60 of about 4,126,170 (169)
Contextual Multi-Armed Bandits for Link Adaptation in Cellular Networks
Proceedings of the 2019 Workshop on Network Meets AI & ML - NetAI'19, 2019 Cellular networks dynamically adjust the transmission parameters for a wireless link in response to its time-varying channel state. This is known as link adaptation, where the typical goal is to maximize the link throughput. State-of-the-art outer loop link adaptation (OLLA) selects the optimal transmission parameters based on an approximate, offline ...
Vidit Saxena +5 more
openaire +3 more sources
Mean‐Variance Payoff Applied to Stackelberg Games
Mathematical Methods in the Applied Sciences, Volume 49, Issue 10, Page 11516-11533, 15 July 2026.ABSTRACT We analyse a Stackelberg duopoly in which the leader faces uncertainty about the intercept demand, while the follower observes the realised demand and decides whether to enter the market after the uncertainty is resolved. The leader evaluates the uncertainty by maximising a mean‐variance utility function that captures its risk aversion.
João M. Silva +3 more
wiley +1 more source
International Journal of Imaging Systems and Technology, Volume 36, Issue 4, July 2026.ABSTRACT Gliomas are aggressive brain tumors that require accurate imaging‐based diagnosis, where automated segmentation plays a central role in assessing tumor morphology and guiding treatment decisions. Manual delineation of gliomas is time‐consuming and prone to variability, motivating the use of deep learning to improve consistency and alleviate ...
Cecilia Diana‐Albelda +4 more
wiley +1 more source
Budget-limited multi-armed bandits [PDF]
, 2012 Decision making under uncertainty is one of the most important challenges within the research field of artificial intelligence, as they present many everyday situations that agents have to face.
Tran-Thanh, Long
core +1 more source
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
wiley +1 more source
Evolutionary Multi-Armed Bandits with Genetic Thompson Sampling [PDF]
, 2022 As two popular schools of machine learning, online learning and evolutionary computations have become two important driving forces behind real-world decision making engines for applications in biomedicine, economics, and engineering fields.
Lin, Baihan
core
Locally Private Nonparametric Contextual Multi-armed Bandits
CoRRMotivated by privacy concerns in sequential decision-making on sensitive data, we address the challenge of nonparametric contextual multi-armed bandits (MAB) under local differential privacy (LDP). We develop a uniform-confidence-bound-type estimator, showing its minimax optimality supported by a matching minimax lower bound.
Yuheng Ma 0001 +4 more
openaire +4 more sources
Strategic Adaptation in Shifting Landscapes: A Paradox‐Theoretic and Computational Perspective
Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l'Administration, Volume 43, Issue 2, June 2026.ABSTRACT Organizations must simultaneously exploit current competencies and explore new opportunities—yet theory offers limited guidance on when each strategic logic dominates and under what combination of environmental conditions ambidexterity is warranted.
Javad Feiz Abadi
wiley +1 more source
RAAS: Runtime Adaptive Approximation System
Concurrency and Computation: Practice and Experience, Volume 38, Issue 12, June 2026.ABSTRACT Software‐level approximation techniques, such as loop perforation and functional replacement, can improve energy and performance in error‐tolerant applications, but typically require extensive programmer intervention even when compiler support is available.
Lucas Reis, Sandro Rigo, Lucas Wanner
wiley +1 more source
SAMBA: A System for Secure Federated Multi-Armed Bandits
, 2022 International audienceThe federated learning paradigm allows several data owners to contribute to a machine learning task without exposing their potentially sensitive data.
Soare, Marta +9 more
core +1 more source