|
|
Analysis of Outlier Detection Methods
Labaš, Dominik ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
The topic of this thesis is analysis of methods for detection of outliers. Firstly, a description of outliers and various methods for their detection is provided. Then a description of selected data sets for testing of methods for detection of outliers is given. Next, an application design for the analysis of the described methods is presented. Then, technologies are presented, which provide models for described methods of detection of outliers. The implementation is then described in more detail. Subsequently, the results of experiments are presented, which represent the main part of this thesis. The results are evaluated and the individual models are compared with each other. Lastly, a method for accelerating outlier detection is demonstrated.
|
|
|
Neural Language Model Acceleration
Labaš, Dominik ; Černocký, Jan (referee) ; Beneš, Karel (advisor)
This work adresses the topic of neural language model acceleration. The aim of this work is to optimize model of a feed-forward neural network. In accelerating of the neural network we used a change of activation function, pre-calculation of matrices for calculationg the hidden layer, implementation of the model's history cache and unnormalized model. The best-performing model was accelerated by 75.3\%.
|
|
|
Analysis of Outlier Detection Methods
Labaš, Dominik ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
The topic of this thesis is analysis of methods for detection of outliers. Firstly, a description of outliers and various methods for their detection is provided. Then a description of selected data sets for testing of methods for detection of outliers is given. Next, an application design for the analysis of the described methods is presented. Then, technologies are presented, which provide models for described methods of detection of outliers. The implementation is then described in more detail. Subsequently, the results of experiments are presented, which represent the main part of this thesis. The results are evaluated and the individual models are compared with each other. Lastly, a method for accelerating outlier detection is demonstrated.
|
|
|
Neural Language Model Acceleration
Labaš, Dominik ; Černocký, Jan (referee) ; Beneš, Karel (advisor)
This work adresses the topic of neural language model acceleration. The aim of this work is to optimize model of a feed-forward neural network. In accelerating of the neural network we used a change of activation function, pre-calculation of matrices for calculationg the hidden layer, implementation of the model's history cache and unnormalized model. The best-performing model was accelerated by 75.3\%.
|
guest ::
