Essays about: "Label acquisition"

Showing result 1 - 5 of 6 essays containing the words Label acquisition.

  1. 1. Representation learning for single cell morphological phenotyping

    University essay from Umeå universitet/Institutionen för fysik

    Author : Andreas Nenner; [2022]
    Keywords : Deep learning; Image-based profiling;

    Abstract : Preclinical research for developing new drugs is a long and expensive procedure. Experiments relying on image acquisition and analysis tend to be low throughput and use reporter systems that may influence the studied cells. READ MORE

  3. 2. A general deep probabilistic model for customer lifetime value prediction of companies : A unified evaluation metric and analysis of the required historical data for different companies in context of prediction of customer lifetime value

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Johanna Olnén; [2022]
    Keywords : ;

    Abstract : A comprehensive understanding of customers’ future Lifetime Value (LTV) enables companies to assess the return on marketing investment and may provide a useful tool when determining a company’s value. Furthermore, LTV predictions allow marketers to segment customers based on the predicted LTV and, in turn, effectively allocate marketing resources for acquisition, retention, and cross-selling. READ MORE

  4. 3. Active Learning for Extractive Question Answering

    University essay from Linköpings universitet/Statistik och maskininlärning

    Author : Salvador Marti Roman; [2022]
    Keywords : Machine Learning; Deep Learning; Active Learning; Natural Language Processing; NLP; Question Answering; Transformers; Uncertainty; Language Models;

    Abstract : Data labelling for question answering tasks (QA) is a costly procedure that requires oracles to read lengthy excerpts of texts and reason to extract an answer for a given question from within the text. QA is a task in natural language processing (NLP), where a majority of recent advancements have come from leveraging the vast corpora of unlabelled and unstructured text available online. READ MORE

  5. 4. Automatic vs. Manual Data Labeling : A System Dynamics Modeling Approach

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : Clas Blank; [2020]
    Keywords : System Dynamics; Modeling; Data Annotation; Data Labeling; Cost Comparison; Systemdynamik; Modellering; Dataannotation; Kostnadsjämförelse;

    Abstract : Labeled data, which is a collection of data samples that have been tagged with one or more labels, play an important role many software organizations in today's market. It can help in solving automation problems, training and validating machine learning models, or analysing data. READ MORE

  6. 5. Active Learning using a Sample Selector Network

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Run Yan Tan; [2020]
    Keywords : Active Learning; Machine Learning; Label budget; Label acquisition; Informative samples; Aktivt Lärande; Maskininlärning; Etikettbudget; Etikettförvärv; Informativa prover;

    Abstract : In this work, we set the stage of a limited labelling budget and propose using a sample selector network to learn and select effective training samples, whose labels we would then acquire to train the target model performing the required machine learning task. We make the assumption that the sample features, the state of the target model and the training loss of the target model are informative for training the sample selector network. READ MORE