Jacek Dabrowski

Orcid: 0000-0002-1581-2365

Affiliations:
  • Synerise, Kraków, Poland


According to our database1, Jacek Dabrowski authored at least 17 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2023
Temporal graph models fail to capture global temporal dynamics.
CoRR, 2023

Synerise Monad: A Foundation Model for Behavioral Event Data.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

The Monad Platform - Temporal Aspects in Behavioral Modeling.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
Data modalities, consumer attributes and recommendation performance in the fashion industry.
Electron. Mark., 2022

Identifying Substitute and Complementary Products for Assortment Optimization with Cleora Embeddings.
Proceedings of the International Joint Conference on Neural Networks, 2022

Synerise Monad - Real-Time Multimodal Behavioral Modeling.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
T-EMDE: Sketching-based global similarity for cross-modal retrieval.
CoRR, 2021

Cleora: A Simple, Strong and Scalable Graph Embedding Scheme.
CoRR, 2021

Modeling Multi-Destination Trips with Sketch-Based Model.
Proceedings of the Workshop on Web Tourism co-located with the 14th ACM International WSDM Conference (WSDM 2021), 2021

Synerise at RecSys 2021: Twitter user engagement prediction with a fast neural model.
Proceedings of the RecSys Challenge 2021: Proceedings of the Recommender Systems Challenge 2021, 2021

On the Unreasonable Effectiveness of Centroids in Image Retrieval.
Proceedings of the Neural Information Processing - 28th International Conference, 2021

Cleora: A Simple, Strong and Scalable Graph Embedding Scheme.
Proceedings of the Neural Information Processing - 28th International Conference, 2021

An Efficient Manifold Density Estimator for All Recommendation Systems.
Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020
I know why you like this movie: Interpretable Efficient Multimodal Recommender.
CoRR, 2020

An efficient manifold density estimator for all recommendation systems.
CoRR, 2020

Multi-modal Embedding Fusion-based Recommender.
CoRR, 2020

A Strong Baseline for Fashion Retrieval with Person Re-identification Models.
Proceedings of the Neural Information Processing - 27th International Conference, 2020


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