{"oa_version":"None","department":[{"_id":"ChLa"}],"doi":"10.1007/978-3-031-40773-4_6","date_updated":"2023-10-09T06:48:02Z","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":"     14068","citation":{"ieee":"P. Tomaszewska and C. Lampert, “On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift,” in <i>International Workshop on Reproducible Research in Pattern Recognition</i>, Montreal, Canada, 2023, vol. 14068, pp. 67–73.","apa":"Tomaszewska, P., &#38; Lampert, C. (2023). On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift. In <i>International Workshop on Reproducible Research in Pattern Recognition</i> (Vol. 14068, pp. 67–73). Montreal, Canada: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-031-40773-4_6\">https://doi.org/10.1007/978-3-031-40773-4_6</a>","chicago":"Tomaszewska, Paulina, and Christoph Lampert. “On the Implementation of Baselines and Lightweight Conditional Model Extrapolation (LIMES) under Class-Prior Shift.” In <i>International Workshop on Reproducible Research in Pattern Recognition</i>, 14068:67–73. Springer Nature, 2023. <a href=\"https://doi.org/10.1007/978-3-031-40773-4_6\">https://doi.org/10.1007/978-3-031-40773-4_6</a>.","ama":"Tomaszewska P, Lampert C. On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift. In: <i>International Workshop on Reproducible Research in Pattern Recognition</i>. Vol 14068. Springer Nature; 2023:67-73. doi:<a href=\"https://doi.org/10.1007/978-3-031-40773-4_6\">10.1007/978-3-031-40773-4_6</a>","short":"P. Tomaszewska, C. Lampert, in:, International Workshop on Reproducible Research in Pattern Recognition, Springer Nature, 2023, pp. 67–73.","mla":"Tomaszewska, Paulina, and Christoph Lampert. “On the Implementation of Baselines and Lightweight Conditional Model Extrapolation (LIMES) under Class-Prior Shift.” <i>International Workshop on Reproducible Research in Pattern Recognition</i>, vol. 14068, Springer Nature, 2023, pp. 67–73, doi:<a href=\"https://doi.org/10.1007/978-3-031-40773-4_6\">10.1007/978-3-031-40773-4_6</a>.","ista":"Tomaszewska P, Lampert C. 2023. On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift. International Workshop on Reproducible Research in Pattern Recognition. RRPR: Reproducible Research in Pattern Recognition, LNCS, vol. 14068, 67–73."},"title":"On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift","article_processing_charge":"No","publication_identifier":{"isbn":["9783031407727"],"eissn":["1611-3349"],"issn":["0302-9743"]},"_id":"14410","scopus_import":"1","date_published":"2023-08-20T00:00:00Z","status":"public","volume":14068,"conference":{"start_date":"2022-08-21","name":"RRPR: Reproducible Research in Pattern Recognition","location":"Montreal, Canada","end_date":"2022-08-21"},"quality_controlled":"1","publisher":"Springer Nature","abstract":[{"text":"This paper focuses on the implementation details of the baseline methods and a recent lightweight conditional model extrapolation algorithm LIMES [5] for streaming data under class-prior shift. LIMES achieves superior performance over the baseline methods, especially concerning the minimum-across-day accuracy, which is important for the users of the system. In this work, the key measures to facilitate reproducibility and enhance the credibility of the results are described.","lang":"eng"}],"year":"2023","date_created":"2023-10-08T22:01:18Z","month":"08","alternative_title":["LNCS"],"publication_status":"published","page":"67-73","author":[{"full_name":"Tomaszewska, Paulina","last_name":"Tomaszewska","first_name":"Paulina"},{"full_name":"Lampert, Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","first_name":"Christoph","last_name":"Lampert","orcid":"0000-0001-8622-7887"}],"language":[{"iso":"eng"}],"day":"20","publication":"International Workshop on Reproducible Research in Pattern Recognition"}