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Results: 1,032
Number of items: 1,032
  • Open Access
    Hendriksen, M. Y. (2024). Multimodal machine learning for information retrieval: A vision and language perspective. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Deffayet, R. E. (2024). Taming the dynamics of recommender systems. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Siro, C., Aliannejadi, M., & de Rijke, M. (2024). Understanding and Predicting User Satisfaction with Conversational Recommender Systems. ACM Transactions on Information Systems, 42(2), Article 55. https://doi.org/10.1145/3624989
  • Open Access
    Li, M. (2024). Repetition and exploration in recommendation. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Deng, S., Sprangers, O., Li, M., Schelter, S., & de Rijke, M. (2024). Domain Generalization in Time Series Forecasting. ACM Transactions on Knowledge Discovery from Data, 18(5), Article 113. https://doi.org/10.1145/3643035
  • Open Access
    Bleeker, M. J. R. (2024). Multi-modal learning algorithms for sequence modeling and representation learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Kersbergen, B., Sprangers, O., Kootte, F., Guha, S., de Rijke, M., & Schelter, S. (2024). Etude - Evaluating the Inference Latency of Session-Based Recommendation Models at Scale. In 2024 IEEE 40th International Conference on Data Engineering: ICDE 2024 : 13-17 May 2024, Utrecht, Netherlands : proceedings (pp. 5177-5183). IEEE Computer Society. https://doi.org/10.1109/icde60146.2024.00389
  • Open Access
    Sprangers, O., Wadman, W., Schelter, S., & de Rijke, M. (2024). Hierarchical forecasting at scale. International Journal of Forecasting, 40(4), 1689-1700. https://doi.org/10.1016/j.ijforecast.2024.02.006
  • Open Access
    Chen, X., Liao, B., Qi, J., Eustratiadis, P., Monz, C., Bisazza, A., & de Rijke, M. (2024). The SIFo Benchmark: Investigating the Sequential Instruction Following Ability of Large Language Models. In Y. Al-Onaizan, M. Bansal, & Y.-N. Chen (Eds.), The 2024 Conference on Empirical Methods in Natural Language Processing : Findings of EMNLP 2024: EMNLP 2024 : November 12-16, 2024 (pp. 1691-1706). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-emnlp.92
  • Open Access
    Rus, C., Yates, A., & de Rijke, M. (2024). A Study of Pre-processing Fairness Intervention Methods for Ranking People. In N. Goharian, N. Tonellotto, Y. He, A. Lipani, G. McDonald, C. Macdonald, & I. Ounis (Eds.), Advances in Information Retrieval: 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24–28, 2024 : proceedings (Vol. IV, pp. 336–350). (Lecture Notes in Computer Science; Vol. 14611). Springer. https://doi.org/10.1007/978-3-031-56066-8_26
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