29 citations · 116 across the 16 of their papers we have counts for
19 papers
Representation Learning for Efficient and Effective Similarity Search and Recommendation
Casper Hansen
How data is represented and operationalized is critical for building computational solutions that are both effective and efficient. A common approach is to represent data objects a…
Automatic Fake News Detection: Are Models Learning to Reason?
Casper Hansen, Christian Hansen, Lucas Chaves Lima
Most fact checking models for automatic fake news detection are based on reasoning: given a claim with associated evidence, the models aim to estimate the claim veracity based on t…
Unsupervised Multi-Index Semantic Hashing
Christian Hansen, Casper Hansen, Jakob Grue Simonsen +2
Semantic hashing represents documents as compact binary vectors (hash codes) and allows both efficient and effective similarity search in large-scale information retrieval. The sta…
Projected Hamming Dissimilarity for Bit-Level Importance Coding in Collaborative Filtering
Christian Hansen, Casper Hansen, Jakob Grue Simonsen +1
When reasoning about tasks that involve large amounts of data, a common approach is to represent data items as objects in the Hamming space where operations can be done efficiently…
Multi-Head Self-Attention with Role-Guided Masks
Dongsheng Wang, Casper Hansen, Lucas Chaves Lima +4
The state of the art in learning meaningful semantic representations of words is the Transformer model and its attention mechanisms. Simply put, the attention mechanisms learn to a…
Denmark's Participation in the Search Engine TREC COVID-19 Challenge: Lessons Learned about Searching for Precise Biomedical Scientific Information on COVID-19
Lucas Chaves Lima, Casper Hansen, Christian Hansen +5
This report describes the participation of two Danish universities, University of Copenhagen and Aalborg University, in the international search engine competition on COVID-19 (the…