Results 31 to 40 of about 2,324,497 (297)

Statistical Risk Models [PDF]

SSRN Electronic Journal, 2016
44 pages; a trivial typo corrected, references updated; to appear in The Journal of Investment Strategies.
Kakushadze, Zura, Yu, Willie
openaire   +2 more sources

Spatio-Temporal Analysis of Urban Heatwaves Using Tukey g-and-h Random Field Models

IEEE Access, 2021
Real-time heatwave risk management with fine-grained spatial resolution is important for analysis of urban heat island (UHI) effects and local heatwaves.
Daisuke Murakami, Gareth W. Peters, Tomoko Matsui, Yoshiki Yamagata   +3 more
doaj   +1 more source

Adaptive Differential Privacy Cox-MLP Model Based on Federated Learning

Mathematics
In the data-driven healthcare sector, balancing privacy protection and model performance is critical. This paper enhances accuracy and reliability in survival analysis by integrating differential privacy, deep learning, and the Cox proportional hazards ...
Jie Niu, Runqi He, Qiyao Zhou, Wenjing Li, Ruxian Jiang, Huimin Li, Dan Chen   +6 more
doaj   +1 more source

Statistical Model Checking of e-Motions Domain-Specific Modeling Languages [PDF]

, 2016
Domain experts may use novel tools that allow them to de- sign and model their systems in a notation very close to the domain problem. However, the use of tools for the statistical analysis of stochas- tic systems requires software engineers to carefully
Alvarez-Palomo, Jose Maria, Durán, Francisco, Moreno-Delgado, Antonio   +2 more
core   +1 more source

adabmDCA: adaptive Boltzmann machine learning for biological sequences

BMC Bioinformatics, 2021
Background Boltzmann machines are energy-based models that have been shown to provide an accurate statistical description of domains of evolutionary-related protein and RNA families.
Anna Paola Muntoni, Andrea Pagnani, Martin Weigt, Francesco Zamponi   +3 more
doaj   +1 more source

Statistical Language Modelling [PDF]

, 2003
Grammar-based natural language processing has reached a level where it can ‘understand’ language to a limited degree in restricted domains. For example, it is possible to parse textual material very accurately and assign semantic relations to parts of sentences.
Gotoh, Yoshihiko, Renals, Steve
openaire   +3 more sources

Music Genre and Emotion Recognition Using Gaussian Processes

IEEE Access, 2014
Gaussian Processes (GPs) are Bayesian nonparametric models that are becoming more and more popular for their superior capabilities to capture highly nonlinear data relationships in various tasks, such as dimensionality reduction, time series analysis ...
Konstantin Markov, Tomoko Matsui
doaj   +1 more source

Federated Learning Based on Kernel Local Differential Privacy and Low Gradient Sampling

IEEE Access
Federated learning that is an approach to addressing the “data silo” problem in a collaborative fashion may face the risk of data leakage in real-world contexts.
Yi Chen, Dan Chen, Niansheng Tang
doaj   +1 more source

Why estimands are needed to define treatment effects in clinical trials

BMC Medicine, 2023
Background The estimand for a clinical trial is a precise definition of the treatment effect to be estimated. Traditionally, estimates of treatment effects are based on either an ITT analysis or a per-protocol analysis.
Oliver N. Keene, Helle Lynggaard, Stefan Englert, Vivian Lanius, David Wright   +4 more
doaj   +1 more source

Extension of Information Geometry to Non-statistical Systems: Some Examples

, 2015
Our goal is to extend information geometry to situations where statistical modeling is not obvious. The setting is that of modeling experimental data. Quite often the data are not of a statistical nature.
A Aspect, C Guerlin, D Petz, J Naudts, J Naudts, J Naudts, JF Clauser, K Huang, L Accardi, L Accardi, M Ohya, MA Nielsen, P Ghose, S Amari, Y Aharonov, Y Aharonov   +15 more
core   +1 more source