no code implementations • 3 Jan 2023 • Elie Azeraf, Emmanuel Monfrini, Wojciech Pieczynski
Practitioners use Hidden Markov Models (HMMs) in different problems for about sixty years.
no code implementations • 3 Jan 2022 • Elie Azeraf, Emmanuel Monfrini, Wojciech Pieczynski
A discriminative model is directly given by $p(x | y)$, which is used to compute discriminative classifiers.
no code implementations • 14 Nov 2021 • Elie Azeraf, Emmanuel Monfrini, Wojciech Pieczynski
HMCs belong to the family of generative models and they are often compared to discriminative models, like conditional random fields (CRFs).
no code implementations • 14 Nov 2021 • Elie Azeraf, Emmanuel Monfrini, Wojciech Pieczynski
Naive Bayes is a popular probabilistic model appreciated for its simplicity and interpretability.
no code implementations • 17 Feb 2021 • Elie Azeraf, Emmanuel Monfrini, Emmanuel Vignon, Wojciech Pieczynski
However, if many works create extensions and improvements of the RNN, few have focused on developing other ways for sequential data processing with neural networks in a "term-to-term" way.
no code implementations • 17 Feb 2021 • Elie Azeraf, Emmanuel Monfrini, Emmanuel Vignon, Wojciech Pieczynski
Natural Language Processing (NLP) models' current trend consists of using increasingly more extra-data to build the best models as possible.
no code implementations • 25 Dec 2020 • Elie Azeraf, Emmanuel Monfrini, Wojciech Pieczynski
Related to this point, we show that the Logistic Regression can be viewed as a particular case of the Naive Bayes used in a discriminative way.
no code implementations • 21 May 2020 • Elie Azeraf, Emmanuel Monfrini, Emmanuel Vignon, Wojciech Pieczynski
We illustrate the efficiency of HMC using EFB in Part-Of-Speech Tagging, showing its superiority over MEMM based restoration.