Results 151 to 160 of about 40,132 (204)

Caution Ahead: Numerical Reasoning and Look‐Ahead Bias in AI Models

Journal of Accounting Research, Volume 64, Issue 3, Page 1139-1188, June 2026.
ABSTRACT Recent work within accounting and finance has highlighted that modern AI systems exhibit superhuman performance on a variety of foundational activities within these fields. However, the literature often does not provide economic rationale for why AI models seem to outperform, largely because these models are a black box.
BRADFORD LEVY
wiley   +1 more source

Dynamic Pricing With Recommendation and Consumer Feedback

The RAND Journal of Economics, Volume 57, Issue 2, Page 349-367, Summer 2026.
ABSTRACT A long‐lived seller sells a new product of unknown value by offering prices and recommendations to short‐lived consumers in continuous time. The seller receives consumer feedback about the product at a rate that increases with the instantaneous sales volume.
Wenji Xu, Shuoguang Yang
wiley   +1 more source

Bayesian Decision Thresholds for Bushfire Warnings: Calibration and Robustness for Rare‐Event Risk

Australian &New Zealand Journal of Statistics, Volume 68, Issue 2, June 2026.
ABSTRACT Current bushfire warning systems communicate the probability of a warning given danger, but residents require the probability of danger given a warning. This misalignment, combined with the extreme rarity of catastrophic fires, often leads to the dangerous ‘wait and see’ behaviour.
Miodrag Lovric, Ojas Davé
wiley   +1 more source

Bayes' theorem and the physical examination: probability assessment and diagnostic decision making. [PDF]

Acad Med, 2011
Herrle SR, Corbett EC, Fagan MJ, Moore CG, Elnicki DM.   +4 more
europepmc   +1 more source

A Probabilistic Greedy Attempt to Be Fair in Neural Team Recommendation

Computational Intelligence, Volume 42, Issue 3, June 2026.
ABSTRACT Neural team recommendation has brought state‐of‐the‐art efficacy while enhancing efficiency at forming teams of experts whose success in completing complex tasks is almost surely guaranteed. However, they overlook fairness, that is, predicted teams are heavily biased toward popular and male experts, falling short of recommending female or ...
Hamed Loghmani, Mahdis Saeedi, Gabriel Rueda, Edwin Paul, Hossein Fani   +4 more
wiley   +1 more source

New Heuristics for Stable LDA Parameter Search

Computational Intelligence, Volume 42, Issue 3, June 2026.
ABSTRACT The Latent Dirichlet Allocation (LDA) algorithm automatically extracts latent topics from a textual corpus, but configuring its parameters can be difficult and time‐consuming. Optimization algorithms can help determine the best parameters, but not necessarily the optimal ones.
Simon‐Olivier Harel, Erick Velazquez‐Godinez, Sylvie Ratté   +2 more
wiley   +1 more source

A Bayesian‐Based Integrative Bioinformatics Analysis Nominates Oncogenic Drivers in Neuroblastoma

Clinical and Translational Science, Volume 19, Issue 6, June 2026.
ABSTRACT Identifying targetable oncogenic drivers remains a challenge in neuroblastoma, the most common extracranial solid malignancy in children. We applied a Bayesian algorithm for integrative analysis of expression and copy‐number, iExCN, to nominate oncogenic drivers in neuroblastoma.
Lin Xu, Arhanti Sadanand, Evan W. Neczypor, Yen‐Ting Liu, Erin Butler, Kelley Moore, Flannery Bowman, Yamin Mazumder, Arlene Naranjo, Alexandre Chlenski, Xue Xiao, Lei Guo, Susan L. Cohn, Mark A. Applebaum, Stephen X. Skapek   +14 more
wiley   +1 more source

Analyzing Non‐Random Selectivity in Online Job Advertisements Using Eurostat Benchmark Data and Generalized Sample Selection Models: An Application to EU Regional Labor Markets

LABOUR, Volume 40, Issue 2, Page 131-161, June 2026.
ABSTRACT The present paper provides an overall framework to afford the problem of non‐representativeness and non‐random selectivity arising from online job ads data, using Generalized sample selection models and Eurostat benchmark data. We jointly model the outcome intensity (number of online job ads in observed profiles, whose levels are defined by ...
Pietro Giorgio Lovaglio, Mario Mezzanzanica   +1 more
wiley   +1 more source

Bayesian Inference for Joint Estimation Models Using Copulas to Handle Endogenous Regressors

Oxford Bulletin of Economics and Statistics, Volume 88, Issue 3, Page 519-534, June 2026.
ABSTRACT This study proposes a Bayesian approach for finite‐sample inference of the Gaussian copula endogeneity correction. Extant studies use frequentist inference, build on a priori computed estimates of marginal distributions of explanatory variables, and use bootstrapping to obtain standard errors. The proposed Bayesian approach facilitates precise
Rouven E. Haschka
wiley   +1 more source

Bayes at the Bedside: Biomarkers in Situations of Clinical Uncertainty. [PDF]

Diagnostics (Basel)
Zettl UK, Hecker M.
europepmc   +1 more source