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Document type:
Bachelorarbeit 
Author(s):
Mihai Zorca 
E-mail address:
mihai@zorca.de 
Title:
Training Deep Convolutional Neural Networks on the GPU Using a Second-Order Optimizer 
Abstract:
Deep Convolutional Neural Networks (CNNs) are a prominent class of powerful and flexible machine learning models. Training such networks requires vast compute resources: due to the large amount of training data and due to the many training it- erations. To speed up learning, many specialized algorithms have been developed. First-order methods (using just the gradient) are the most popular, but second-order algorithms (using Hessian information) are gaining importance. In this thesis we give...    »
 
Supervisor:
Hans-Joachim Bungartz 
Advisor:
Severin Reiz 
Year:
2020 
Quarter:
3. Quartal 
Year / month:
2020-07 
Month:
Jul 
Pages:
54 
Language:
en 
University:
TUM