Essays about: "Transformer"
Showing result 16 - 20 of 373 essays containing the word Transformer.
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16. Active learning for text classification in cyber security
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In the domain of cyber security, machine learning promises advanced threat detection. However, the volume of available unlabeled data poses challenges for efficient data management. This study investigates the potential for active learning, a subset of interactive machine learning, to reduce the effort required for manual data labelling. READ MORE
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17. Transformer Offline Reinforcement Learning for Downlink Link Adaptation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Recent advancements in Transformers have unlocked a new relational analysis technique for Reinforcement Learning (RL). This thesis researches the models for DownLink Link Adaptation (DLLA). READ MORE
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18. Utilizing Transformers with Domain-Specific Pretraining and Active Learning to Enable Mining of Product Labels
University essay from Uppsala universitet/Avdelningen för beräkningsvetenskapAbstract : Structured Product Labels (SPLs), the package inserts that accompany drugs governed by the Food and Drugs Administration (FDA), hold information about Adverse Drug Reactions (ADRs) that exists associated with drugs post-market. This information is valuable for actors working in the field of pharmacovigilance aiming to improve the safety of drugs. READ MORE
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19. Domain Knowledge and Representation Learning for Centroid Initialization in Text Clustering with k-Means : An exploratory study
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Text clustering is a problem where texts are partitioned into homogeneous clusters, such as partitioning them based on their sentiment value. Two techniques to address the problem are representation learning, in particular language representation models, and clustering algorithms. READ MORE
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20. Detection of insurance fraud using NLP and ML
University essay from Lunds universitet/Matematisk statistikAbstract : Machine-Learning can sometimes see things we as humans can not. In this thesis we evaluated three different Natural Language Procces-techniques: BERT, word2vec and linguistic analysis (UDPipe), on their performance in detecting insurance fraud based on transcribed audio from phone calls (referred to as audio data) and written text (referred to as text-form data), related to insurance claims. READ MORE
