Reconet: An interpretable neural architecture for recommender systems
- Francesco Fusco
- Michalis Vlachos
- et al.
- 2019
- IJCAI 2019
Conference paper
Publications
59 results for Michalis Vlachos
Addressing Interpretability and Cold-Start in Matrix Factorization for Recommender Systems
- Michalis Vlachos
- Celestine Mendler-Dünner
- et al.
- 2019
- IEEE TKDE
PaperTopic modeling based on keywords and context
- Johannes Schneider
- Michalis Vlachos
- 2018
- SDM 2018
Conference paperVery-low random projection maps
- Anastasios Zouzias
- Michalis Vlachos
- 2018
- EDBT 2018
Conference paperHigh-Performance Recommender System Training Using Co-Clustering on CPU/GPU Clusters
- Kubilay Atasu
- Thomas Parnell
- et al.
- 2017
- ICPP 2017
Conference paperLinear-complexity relaxed word Mover's distance with GPU acceleration
- Kubilay Atasu
- Thomas Parnell
- et al.
- 2017
- Big Data 2017
Conference paperScalable and interpretable product recommendations via overlapping co-clustering
- Reinhard Heckel
- Michalis Vlachos
- et al.
- 2017
- ICDE 2017
Conference paperPrivate and right-protected big data publication: An analysis
- Reinhard Heckel
- Michalis Vlachos
- 2017
- SDM 2017
Conference paperScalable density-based clustering with quality guarantees using random projections
- Johannes Schneider
- Michalis Vlachos
- 2017
- Data Mining and Knowledge Discovery
PaperToward interpretable predictive models in B2B recommender systems
- Michalis Vlachos
- Vasileios Vasileiadis
- et al.
- 2016
- IBM J. Res. Dev
Paper