Sökning: "Distributed deep learning architecture"

Visar resultat 6 - 10 av 13 uppsatser innehållade orden Distributed deep learning architecture.

1. 6. Random projections in a distributed environment for privacy-preserved deep learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Malcolm Bagger Toräng; [2021]
   Nyckelord :Random projections; Generative adversarial networks; Privacy metrics; Deep learning; Obfuscation.; Slumpmässiga projektioner; Generativa kontroversiella nätverk; Privatiserings-mått; Djupinlärning; Obfuskering.;

   Sammanfattning : The field of Deep Learning (DL) only over the last decade has proven useful for increasingly more complex Machine Learning tasks and data, a notable milestone being generative models achieving facial synthesis indistinguishable from real faces. With the increased complexity in DL architecture and training data, follows a steep increase in time and hardware resources required for the training task. LÄS MER

3. 7. Comparing a gang-like scheduler with the default Kubernetes scheduler in a multi-tenant serverless distributed deep learning training environment

   Master-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Frans-Lukas Lövenvald; [2021]
   Nyckelord :Deep learning; serverless; scheduling;

   Sammanfattning : Systems for running distributed deep learning training on the cloud have recently been developed. An important component of a distributed deep learning job handler is its resource allocation scheduler. This scheduler allocates computing resources to parts of a distributed training architecture. LÄS MER

4. 8. Investigation and Implementation of Federation Mechanisms of SVP

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Babar Khan; [2020]
   Nyckelord :Bonseyes Marketplace; AI Engineering; Resource Federation; Federation mechanisms; Distributed Secure Virtual Premise;

   Sammanfattning : The development of AI application on the edge devices require integrated data, algorithms, and tools. Big companies like Google and Apple have integrated data, algorithms, and tools for building end to end systems with optimized and dedicated hardware for deep learning applications. LÄS MER

5. 9. Deep learning to classify driver sleepiness from electrophysiological data

   Master-uppsats, Linköpings universitet/Institutionen för medicinsk teknik

   Författare :Ida Johansson; Frida Lindqvist; [2019]
   Nyckelord :Driver Sleepiness Detection; KSS; Signal Processing; Deep Learning; Electrophysiological Signals;

   Sammanfattning : Driver sleepiness is a cause for crashes and it is estimated that 3.9 to 33 % of all crashes might be related to sleepiness at the wheel. It is desirable to get an objective measurement of driver sleepiness for reduced sensitivity to subjective variations. LÄS MER

7. 10. Federated Averaging Deep Q-NetworkA Distributed Deep Reinforcement Learning Algorithm

   Master-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Sebastian Backstad; [2018]
   Nyckelord :;

   Sammanfattning : In the telecom sector, there is a huge amount of rich data generated every day. This trend will increase with the launch of 5G networks. Telco companies are interested in analyzing their data to shape and improve their core businesses. LÄS MER