Search results
Results: 47
Number of items: 47
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Ariannezhad, M., Schelter, S., & de Rijke, M. (2020). Demand Forecasting in the Presence of Privileged Information. In V. Lemaire, S. Malinowski, A. Bagnall, T. Guyet, R. Tavenard, & G. Ifrim (Eds.), Advanced Analytics and Learning on Temporal Data: 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020 : revised selected papers (pp. 46-62). (Lecture Notes in Computer Science; Vol. 12588), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-65742-0_4 -
Anil, R., Capan, G., Drost-Fromm, I., Dunning, T., Friedman, E., Grant, T., Quinn, S., Ranjan, P., Schelter, S., & Yılmazel, Ö. (2020). Apache Mahout: Machine Learning on Distributed Dataflow Systems. Journal of Machine Learning Research, 21, Article 127. https://jmlr.csail.mit.edu/papers/v21/18-800.html
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Schelter, S. (2020). Technical Perspective: Query Optimization for Faster Deep CNN Explanations. SIGMOD Record, 49(1), 60. https://doi.org/10.1145/3422648.3422662
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Schelter, S., & Stoyanovich, J. (2020). Taming Technical Bias in Machine Learning Pipelines. Bulletin of the Technical Committee on Data Engineering, 43(4), 39-50. http://sites.computer.org/debull/A20dec/p39.pdf
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Sarvi, F., Voskarides, N., Mooiman, L., Schelter, S., & de Rijke, M. (2020). A Comparison of Supervised Learning to Match Methods for Product Search. In The 2020 SIGIR Workshop On eCommerce: July 30 : accepted papers Article 30 SIGIR eCom'20. https://sigir-ecom.github.io/ecom20Papers/paper30.pdf
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Hendriksen, M., Kuiper, E., Nauts, P., Schelter, S., & de Rijke, M. (2020). Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers. In The 2020 SIGIR Workshop On eCommerce: July 30 : accepted papers Article 23 SIGIR eCom'20. https://sigir-ecom.github.io/ecom20Papers/paper23.pdf
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Yang, K., Huang, B., Stoyanovich, J., & Schelter, S. (2020). Fairness-Aware Instrumentation of Preprocessing Pipelines for Machine Learning. In HILDA 2020: Workshop on Human-In-the-Loop Data Analytics : co-located with SIGMOD 2020 : 19 June 2020, Portland, OR, USA Article 9 HILDA. https://ssc.io/publication/fairness-aware-instrumentation-of-preprocessing-pipelines-forml-hilda20/
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