Sökning: "Distribuerad maskininlärning"

Visar resultat 11 - 15 av 19 uppsatser innehållade orden Distribuerad maskininlärning.

1. 11. Scalable Hyperparameter Optimization: Combining Asynchronous Bayesian Optimization With Efficient Budget Allocation

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

   Författare :Kai Jeggle; [2020]
   Nyckelord :;

   Sammanfattning : Automated hyperparameter tuning has become an integral part in the optimization of machine learning (ML) pipelines. Sequential model based optimization algorithms, such as bayesian optimization (BO), have been proven to be sample efficient with strong final performance. LÄS MER

3. 12. Scalable Gaussian Process Regression for Time Series Modelling

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

   Författare :Vidhyarthi Boopathi; [2019]
   Nyckelord :Distributed Machine learning; Spark; Gaussian Processes; Regression; Time series; Distribuerad maskininlärning; Spark; Gaussiska processer; Regression; Sensormodellering; Tidsserier;

   Sammanfattning : Machine learning algorithms has its applications in almost all areas of our daily lives. This is mainly due to its ability to learn complex patterns and insights from massive datasets. With the increase in the data at a high rate, it is becoming necessary that the algorithms are resource-efficient and scalable. LÄS MER

4. 13. Information-Theoretic Framework for Network Anomaly Detection: Enabling online application of statistical learning models to high-speed traffic

   Master-uppsats, KTH/Matematisk statistik

   Författare :Gabriel Damour; [2019]
   Nyckelord :Network Security; Distributed Denial of Service; DDoS; DoS; Anomaly Detection; Intrusion Detection; Attack Source Identification; Information Theory; Statistical Learnin; Nätverkssäkerhet; Distribuerad Överbelastningsattack; DDoS; DoS; Anomalidetektering; Intrångsdetektering; Identifiering av Attackkällor; Informationsteori; Maskininlärning;

   Sammanfattning : With the current proliferation of cyber attacks, safeguarding internet facing assets from network intrusions, is becoming a vital task in our increasingly digitalised economies. Although recent successes of machine learning (ML) models bode the dawn of a new generation of intrusion detection systems (IDS); current solutions struggle to implement these in an efficient manner, leaving many IDSs to rely on rule-based techniques. LÄS MER

5. 14. Ablation Programming for Machine Learning

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

   Författare :Sina Sheikholeslami; [2019]
   Nyckelord :Distributed Machine Learning; Distributed Systems; Ablation Studies; Apache Spark; Keras; Hopsworks;

   Sammanfattning : As machine learning systems are being used in an increasing number of applications from analysis of satellite sensory data and health-care analytics to smart virtual assistants and self-driving cars they are also becoming more and more complex. This means that more time and computing resources are needed in order to train the models and the number of design choices and hyperparameters will increase as well. LÄS MER

7. 15. Deep reinforcement learning i distribuerad optimering

   Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)

   Författare :Marcus Lindström; Jahangir Jazayeri; [2018]
   Nyckelord :;

   Sammanfattning : Reinforcement learning has recently become a promising area of machine learning with significant achievements in the subject. Recent successes include surpassing human experts on Atari games and also AlphaGo becoming the first computer ranked on the highest professional level in the game Go, to mention a few. LÄS MER