1 code implementation • 4 Aug 2022 • Carlo Bono, Mehmet Oğuz Mülâyim, Cinzia Cappiello, Mark Carman, JesUs Cerquides, Jose Luis Fernandez-Marquez, Rosy Mondardini, Edoardo Ramalli, Barbara Pernici
However, finding relevant information among millions of posts being posted every day can be difficult, and developing a data analysis project usually requires time and technical skills.
no code implementations • 16 Nov 2021 • JesUs Cerquides
Probabilistic graphical models allow us to encode a large probability distribution as a composition of smaller ones.
no code implementations • 18 May 2021 • JesUs Cerquides
In this paper we leverage on probability over Riemannian manifolds to rethink the interpretation of priors and posteriors in Bayesian inference.
no code implementations • 19 Jan 2020 • Borja Sánchez-López, JesUs Cerquides
Here, we propose a stochastic optimization method for MLR based on manifold optimization concepts which (i) has per-iteration computational complexity is linear in the number of parameters and (ii) can be proven to converge.
no code implementations • 14 Aug 2015 • Jordi Roca-Lacostena, JesUs Cerquides, Marc Pouly
In spite of that, the mainline of Pouly and Kohlas' theory is correct, although some of the necessary conditions have to be revised.
no code implementations • 26 Feb 2014 • Jordi Roca-Lacostena, JesUs Cerquides
Valuation algebras abstract a large number of formalisms for automated reasoning and enable the definition of generic inference procedures.
no code implementations • 28 Aug 2013 • Victor Bellon, JesUs Cerquides, Ivo Grosse
Classifiers based on probabilistic graphical models are very effective.