62 citations · 84 across the 5 of their papers we have counts for
4 papers · 1 filter
Learning similarity measures from data
Bjørn Magnus Mathisen, Agnar Aamodt, Kerstin Bach +1
Defining similarity measures is a requirement for some machine learning methods. One such method is case-based reasoning (CBR) where the similarity measure is used to retrieve the…
Probabilistic Models with Deep Neural Networks
Andrés R. Masegosa, Rafael Cabañas, Helge Langseth +2
Recent advances in statistical inference have significantly expanded the toolbox of probabilistic modeling. Historically, probabilistic modeling has been constrained to (i) very re…
Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention
Ming Zeng, Haoxiang Gao, Tong Yu +4
Deep neural networks, including recurrent networks, have been successfully applied to human activity recognition. Unfortunately, the final representation learned by recurrent netwo…
Bayesian Models of Data Streams with Hierarchical Power Priors
Andres Masegosa, Thomas D. Nielsen, Helge Langseth +3
Making inferences from data streams is a pervasive problem in many modern data analysis applications. But it requires to address the problem of continuous model updating and adapt…