Vojtech Vancura

According to our database, Vojtech Vancura authored at least 14 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

From Knots to Knobs: Towards Steerable Collaborative Filtering Using Sparse Autoencoders.

Martin Spisák, Ladislav Peska, Petr Skoda, Vojtech Vancura, Rodrigo Alves

CoRR, January, 2026

Efficient Learning of Sparse Representations from Interactions.

Vojtech Vancura, Martin Spisák, Rodrigo Alves, Ladislav Peska

Proceedings of the ACM Web Conference 2026, 2026

Leveraging Artist Catalogs for Cold-Start Music Recommendation.

Yan-Martin Tamm, Gregor Meehan, Vojtech Nekl, Vojtech Vancura, Rodrigo Alves, Johan Pauwels, Anna Aljanaki

Proceedings of the 34th ACM Conference on User Modeling, Adaptation and Personalization, 2026

Language Embeddings Meet Shallow Autoencoders.

Rodrigo Alves, Vojtech Vancura, Pavel Kordík, Antoine Ledent

Proceedings of the 34th ACM Conference on User Modeling, Adaptation and Personalization, 2026

2025

Mitigating Risks in Marketplace Semantic Search: A Dataset for Harmful and Sensitive Query Alignment.

Filip Spacek, Vojtech Vancura, Pavel Kordík

Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization, 2025

The Future is Sparse: Embedding Compression for Scalable Retrieval in Recommender Systems.

Petr Kasalický, Martin Spisák, Vojtech Vancura, Daniel Bohunek, Rodrigo Alves, Pavel Kordík

Proceedings of the Nineteenth ACM Conference on Recommender Systems, 2025

Segment-Aware Analytics for Real-Time Editorial Support in Media Groups.

Martin Spisák, Rodrigo Alves, Thomas Kelleher, Jason Sheppard, Ondrej Fiedler, Ergys Kosovrasti, Vojtech Vancura, Petr Kasalický, Pavel Kordík

Proceedings of the 13th International Workshop on News Recommendation and Analytics co-located with the 2025 ACM Conference on Recommender Systems (RecSys 2025), 2025

2024

beeFormer: Bridging the Gap Between Semantic and Interaction Similarity in Recommender Systems.

Vojtech Vancura, Pavel Kordík, Milan Straka

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

2023

Scalable and Explainable Linear Shallow Autoencoders for Collaborative Filtering from Industrial Perspective.

Vojtech Vancura

Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, 2023

2022

Scalable Linear Shallow Autoencoder for Collaborative Filtering.

Vojtech Vancura, Rodrigo Alves, Petr Kasalický, Pavel Kordík

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

RepSys: Framework for Interactive Evaluation of Recommender Systems.

Jan Safarík, Vojtech Vancura, Pavel Kordík

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Offline evaluation of the serendipity in recommendation systems.

Daniil Pastukhov, Stanislav Kuznetsov, Vojtech Vancura, Pavel Kordík

Proceedings of the 17th IEEE International Conference on Computer Sciences and Information Technologies, 2022

2021

Neural Basket Embedding for Sequential Recommendation.

Vojtech Vancura

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Deep Variational Autoencoder with Shallow Parallel Path for Top-N Recommendation (VASP).

Vojtech Vancura, Pavel Kordík

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021