Results 101 to 110 of about 497,803 (209)

BER-Constrained Service-Aware Link Adaptation via Contextual Bandit for Quasi-Stationary SDR-Based Backhaul

IEEE Open Journal of the Communications Society
Conventional Adaptive Modulation and Coding (AMC) schemes generally optimize a common link-level objective, limiting their ability to tailor Modulation and Coding Scheme (MCS) decisions to traffic classes with distinct reliability requirements.
Diego Gabriel Soares Pivoto, Juliano Silveira Ferreira, Matheus Seda Borsato Cunha, Felipe A. P. de Figueiredo, Luciano Leonel Mendes   +4 more
doaj   +1 more source

Development of Elective Flexibility and Related Cognitive Functions Across Three Cultures

Developmental Science, Volume 30, Issue 1, January 2027.
ABSTRACT Elective flexibility, the ability to switch between working strategies adaptively, is critical for decision‐making in complex environments. Here we experimentally assessed elective flexibility alongside three related cognitive measures short‐term memory, inhibition, and responsive flexibility–in 325 children and adults (ages 4–81‐years) from ...
Sarah Pope‐Caldwell, Elisa Felsche, Ardain Dzabatou, Wilson Vieira, Luke Maurits, Dominik Deffner, Daniel Haun   +6 more
wiley   +1 more source

Model Selection in Contextual Stochastic Bandit Problems [PDF]

, 2022
We study bandit model selection in stochastic environments. Our approach relies on a meta-algorithm that selects between candidate base algorithms.
Pacchiano, Aldo, Abbasi-Yadkori, Yasin, Rao, Anup, Lattimore, Tor, Phan, My, Szepesvari, Csaba, Zimmert, Julian   +6 more
core   +1 more source

Gaussian Process with Vine Copula-Based Context Modeling for Contextual Multi-Armed Bandits

Mathematics
We propose a novel contextual multi-armed bandit (CMAB) framework that integrates copula-based context generation with Gaussian Process (GP) regression for reward modeling, addressing complex dependency structures and uncertainty in sequential decision ...
Jong-Min Kim
doaj   +1 more source

A Comprehensive Review on Federated and Incremental Learning in Spatial Crowdsourcing Systems

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 4, December 2026.
A comprehensive overview of Federated and Incremental Learning (FIL) integration in Spatial Crowdsourcing, highlighting privacy, security, adaptability, efficiency challenges, and future research directions. ABSTRACT Spatial Crowdsourcing (SC) coordinates workers and requesters through personal mobile devices to complete location‐dependent tasks in ...
Md Mujibur Rahman, Quazi Mamun, Michael Bewong, Md Zahidul Islam   +3 more
wiley   +1 more source

Contextual bandits to increase user prediction accuracy in movie recommendation system [PDF]

ITM Web of Conferences
Cold-start problems are inevitable phenomena where recommendation systems fail to accurately predict users’ favour and cause the loss of new users. The typical Multi-Armed Bandit (MAB) models are widely adopted as recommendation systems to solve cold ...
Chen Yizhe
doaj   +1 more source

Evaluating Early‐Stage Oncology Clinical Trial Designs in the Era of Project Optimus: A Scoping Review

Pharmaceutical Statistics, Volume 25, Issue 6, November/December 2026.
ABSTRACT In 2021, the FDA initiated Project Optimus to reform dose optimization and selection in early‐phase oncology, highlighting that doses and schedules of new therapies are often inadequately characterized and that traditional dose‐finding approaches should be revised.
Marie‐Karelle Riviere, Anaïs Andrillon, Pavel Mozgunov, Emma Gerard, Moreno Ursino   +4 more
wiley   +1 more source

Joint UAV Trajectory Planning and LEO-Sat Selection in SAGIN

IEEE Open Journal of the Communications Society
In this paper, the problem of joint unmanned aerial vehicle (UAV) trajectory planning and low-orbit satellites (LEO-Sats) selection in space-air-ground integrated networks (SAGIN) will be investigated.
Ehab Mahmoud Mohamed, Mohammad Ahmed Alnakhli, Mostafa M. Fouda   +2 more
doaj   +1 more source

Deepening the real options debate: Real options as dynamic optimization

Strategic Management Journal, Volume 47, Issue 11, Page 2823-2870, November 2026.
Abstract Research Summary Is real option theory useful for management research? This topic was hotly debated two decades ago. Real options were said to be inapplicable to management research and to lack conceptual distinctiveness. Whereas responses to the claim about the non‐distinctiveness of real options were disparate, the concern about the theory's
Arkadiy V. Sakhartov, Joseph T. Mahoney, Jeffrey J. Reuer   +2 more
wiley   +1 more source

Sparse Nonparametric Contextual Bandits

CoRR
We study the benefits of sparsity in nonparametric contextual bandit problems, in which the set of candidate features is countably or uncountably infinite. Our contribution is two-fold. First, using a novel reduction to sequences of multi-armed bandit problems, we provide lower bounds on the minimax regret, which show that polynomial dependence on the ...
Hamish Flynn, Julia Olkhovskaya, Paul Rognon-Vael   +2 more
openaire   +3 more sources