45 citations
- Carl von Ossietzky Universität OldenburgDE46 papers
- Fraunhofer Institute for Digital Media TechnologyDE9 papers
- KU LeuvenBE5 papers
- Aalborg UniversityDK4 papers
- Jade University of Applied SciencesDE4 papers
- Klinikum OldenburgDE4 papers
- University of SouthamptonGB2 papers
- Bang & Olufsen (Denmark)DK1 paper
- Bar-Ilan UniversityIL1 paper
- Christian-Albrechts-Universität zu KielDE1 paper
- Frankfurt Institute for Advanced StudiesDE1 paper
- Goethe University FrankfurtDE1 paper
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2017★ 2 cited
Truncated Variational EM for Semi-Supervised Neural Simpletrons
Dennis Forster, Jörg Lücke
Inference and learning for probabilistic generative networks is often very challenging and typically prevents scalability to as large networks as used for deep discriminative appro…
stat.ML2015★ 15 cited
Neural Simpletrons - Minimalistic Directed Generative Networks for Learning with Few Labels
Dennis Forster, Abdul-Saboor Sheikh, Jörg Lücke
Classifiers for the semi-supervised setting often combine strong supervised models with additional learning objectives to make use of unlabeled data. This results in powerful thoug…
stat.ML2012
A Truncated EM Approach for Spike-and-Slab Sparse Coding
Abdul-Saboor Sheikh, Jacquelyn A. Shelton, Jörg Lücke
We study inference and learning based on a sparse coding model with `spike-and-slab' prior. As in standard sparse coding, the model used assumes independent latent sources that lin…