4 papers
Favour: FAst Variance Operator for Uncertainty Rating
Thomas D. Ahle, Sahar Karimi, Peter Tak Peter Tang
Bayesian Neural Networks (BNN) have emerged as a crucial approach for interpreting ML predictions. By sampling from the posterior distribution, data scientists may estimate the unc…
Similarity Search with Tensor Core Units
Thomas D. Ahle, Francesco Silvestri
Tensor Core Units (TCUs) are hardware accelerators developed for deep neural networks, which efficiently support the multiplication of two dense matrices,…
On the Problem of in Locality-Sensitive Hashing
Thomas Dybdahl Ahle
A Locality-Sensitive Hash (LSH) function is called -sensitive, if two data-points with a distance less than collide with probability at least while data p…
Subsets and Supermajorities: Optimal Hashing-based Set Similarity Search
Thomas Dybdahl Ahle, Jakob Bæk Tejs Knudsen
We formulate and optimally solve a new generalized Set Similarity Search problem, which assumes the size of the database and query sets are known in advance. By creating polylog co…