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researcher

M. Speranskaya

2 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author1

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedRanking vs. Classifying: Measuring Knowledge Base Completion Quality

3 citations · 3 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2021

Knodle: Modular Weakly Supervised Learning with PyTorch

Anastasiia Sedova, Andreas Stephan, Marina Speranskaya +1

Strategies for improving the training and prediction quality of weakly supervised machine learning models vary in how much they are tailored to a specific task or integrated with a…

cs.AI2021★ 3 cited

Ranking vs. Classifying: Measuring Knowledge Base Completion Quality

Marina Speranskaya, Martin Schmitt, Benjamin Roth

Knowledge base completion (KBC) methods aim at inferring missing facts from the information present in a knowledge base (KB) by estimating the likelihood of candidate facts. In the…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.