Search Results for author:
Found 7 papers, 2 papers with code
Foundation Models for Natural Language Processing -- Pre-trained Language Models Integrating Media
When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning.
Supporting verification of news articles with automated search for semantically similar articles
We find that our approach is agnostic to concept drifts, i. e. the machine learning task is independent of the hypotheses in a text.
Systematic Comparison of the Influence of Different Data Preprocessing Methods on the Performance of Gait Classifications Using Machine Learning
Therefore, the aim of this analysis is to compare different combinations of commonly applied data preprocessing steps and test their effects on the classification performance of gait patterns.
Improving Word Embeddings Using Kernel PCA
Word-based embedding approaches such as Word2Vec capture the meaning of words and relations between them, particularly well when trained with large text collections; however, they fail to do so with small datasets.
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems
It considers the source of knowledge, its representation, and its integration into the machine learning pipeline.
Corresponding Projections for Orphan Screening
We propose a novel transfer learning approach for orphan screening called corresponding projections.
Making Efficient Use of a Domain Expert's Time in Relation Extraction
In this paper, we report on an alternative approach where we first construct a relation extraction model using distant supervision, and only later make use of a domain expert to refine the results.
