168 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- KTH Royal Institute of TechnologySE17 papers
- Chalmers University of TechnologySE15 papers
- Lund UniversitySE13 papers
- Luleå University of TechnologySE8 papers
- University of California, BerkeleyUS8 papers
- Blekinge Institute of TechnologySE6 papers
- Uppsala UniversitySE6 papers
- National Physical LaboratoryGB5 papers
- University of GothenburgSE5 papers
- Intel (United States)US4 papers
- Istituto Nazionale di Ricerca MetrologicaIT4 papers
- Physikalisch-Technische BundesanstaltDE4 papers
4 papers · 2 filters
On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks
Antonello Rosato, Massimo Panella, Evgeny Osipov +1
A change of the prevalent supervised learning techniques is foreseeable in the near future: from the complex, computational expensive algorithms to more flexible and elementary tra…
Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing
Cameron Diao, Denis Kleyko, Jan M. Rabaey +1
Machine learning algorithms deployed on edge devices must meet certain resource constraints and efficiency requirements. Random Vector Functional Link (RVFL) networks are favored f…
Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks
Jens Henriksson, Christian Berger, Markus Borg +3
Several areas have been improved with Deep Learning during the past years. For non-safety related products adoption of AI and ML is not an issue, whereas in safety critical applica…
Auto-weighted Robust Federated Learning with Corrupted Data Sources
Shenghui Li, Edith Ngai, Fanghua Ye +1
Federated learning provides a communication-efficient and privacy-preserving training process by enabling learning statistical models with massive participants while keeping their…