The analysis of discrimination, feature and model selection conduct to the discussion of the relationships between Support Vector Machine (SVM), Bayesian and Maximum Entropy (MaxEnt) formalisms
We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic model...
We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic model...
We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic model...
We present a general framework for discriminative estimation based on the maximum en-tropy principle...
Incorporating feature selection into a classi cation or regression method often carries anumberofadv...
The maximum entropy (MaxEnt) method is a relatively new technique especially suitable for reconstruc...
The Maximum Entropy ($\textit{MaxEnt}$) method is a relatively new technique especially suitable for...
(Jaynes') Method of (Shannon-Kullback's) Relative Entropy Maximization (REM or MaxEnt) can be - at l...
Maximum entropy is a powerful concept that entails a sharp separation between relevant and irrelevan...
Maximum entropy is a powerful concept that entails a sharp separation between relevant and irrelevan...
These proceedings from the 37th International Workshop on Bayesian Inference and Maximum Entropy Met...
We compare the application of Bayesian inference and the maximum entropy (MaxEnt) method for the ana...
This paper describes maxent in detail and presents an Increment Feature Selection algorithm for incr...
The main content of this review article is first to review the main inference tools using Bayes rule...
The main content of this review article is first to review the main inference tools using Bayes rule...
We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic model...
We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic model...
We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic model...
We present a general framework for discriminative estimation based on the maximum en-tropy principle...
Incorporating feature selection into a classi cation or regression method often carries anumberofadv...
The maximum entropy (MaxEnt) method is a relatively new technique especially suitable for reconstruc...
The Maximum Entropy ($\textit{MaxEnt}$) method is a relatively new technique especially suitable for...
(Jaynes') Method of (Shannon-Kullback's) Relative Entropy Maximization (REM or MaxEnt) can be - at l...
Maximum entropy is a powerful concept that entails a sharp separation between relevant and irrelevan...
Maximum entropy is a powerful concept that entails a sharp separation between relevant and irrelevan...
These proceedings from the 37th International Workshop on Bayesian Inference and Maximum Entropy Met...
We compare the application of Bayesian inference and the maximum entropy (MaxEnt) method for the ana...
This paper describes maxent in detail and presents an Increment Feature Selection algorithm for incr...
The main content of this review article is first to review the main inference tools using Bayes rule...
The main content of this review article is first to review the main inference tools using Bayes rule...
We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic model...
We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic model...
We show how the SVM can be viewed as a maximum likelihood estimate of a class of probabilistic model...
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