Essays about: "continual learning"
Showing result 1 - 5 of 15 essays containing the words continual learning.
-
1. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. READ MORE
-
2. A Comparison of CNN and Transformer in Continual Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Within the realm of computer vision tasks, Convolutional Neural Networks (CNN) and Transformers represent two predominant methodologies, often subject to extensive comparative analyses elucidating their respective merits and demerits. This thesis embarks on an exploration of these two models within the framework of continual learning, with a specific focus on their propensities for resisting catastrophic forgetting. READ MORE
-
3. Integration of Continual Learning and Semantic Segmentation in a vision system for mobile robotics
University essay from Luleå tekniska universitet/RymdteknikAbstract : Over the last decade, the integration of robots into various applications has seen significant advancements fueled by Machine Learning (ML) algorithms, particularly in autonomous and independent operations. While robots have become increasingly proficient in various tasks, object instance recognition, a fundamental component of real-world robotic interactions, has witnessed remarkable improvements in accuracy and robustness. READ MORE
-
4. Machines Do Not Have Little Gray Cells: : Analysing Catastrophic Forgetting in Cross-Domain Intrusion Detection Systems
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : Cross-domain intrusion detection, a critical component of cybersecurity, involves evaluating the performance of neural networks across diverse datasets or databases. The ability of intrusion detection systems to effectively adapt to new threats and data sources is paramount for safeguarding networks and sensitive information. READ MORE
-
5. Tackling Non-Stationarity in Reinforcement Learning via Latent Representation : An application to Intraday Foreign Exchange Trading
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Reinforcement Learning has applications in various domains, but the typical assumption is of a stationary process. Hence, when this hypothesis does not hold, performance may be sub-optimal. READ MORE
