From 109044ccc5058e022b1af4862ffdaf701c46abe7 Mon Sep 17 00:00:00 2001 From: Arie van Deursen Date: Wed, 4 Oct 2023 22:07:04 +0200 Subject: [PATCH] Add paper urls --- _tracks/04_deploying_ml_models_at_scale.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/_tracks/04_deploying_ml_models_at_scale.md b/_tracks/04_deploying_ml_models_at_scale.md index bb0b71e..7fae96f 100644 --- a/_tracks/04_deploying_ml_models_at_scale.md +++ b/_tracks/04_deploying_ml_models_at_scale.md @@ -18,11 +18,11 @@ In this track we will seek to address such challenges at ING scale. - Arumoy Shome, Luís Cruz, Arie van Deursen: Towards Understanding Machine Learning Testing in Practise. CAIN 2023: 117-118 -- Lorena Poenaru-Olaru, June Sallou, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen: Retrain AI Systems Responsibly! Use Sustainable Concept Drift Adaptation Techniques. GREENS@ICSE 2023: 17-18 +- Lorena Poenaru-Olaru, June Sallou, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen: Retrain AI Systems Responsibly! Use Sustainable Concept Drift Adaptation Techniques. GREENS@ICSE 2023: 17-18 ([preprint](https://research.tudelft.nl/en/publications/retrain-ai-systems-responsibly-use-sustainable-concept-drift-adap)). - Arumoy Shome, Luís Cruz, Arie van Deursen: Data smells in public datasets. CAIN 2022: 205-216 -- Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen, Jan S. Rellermeyer: Are Concept Drift Detectors Reliable Alarming Systems? - A Comparative Study. IEEE Big Data 2022: 3364-3373 +- Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen, Jan S. Rellermeyer: Are Concept Drift Detectors Reliable Alarming Systems? - A Comparative Study. IEEE Big Data 2022: 3364-3373 ([preprint](https://research.tudelft.nl/en/publications/are-concept-drift-detectors-reliable-alarming-systems-a-comparati)). - Haiyin Zhang, Luís Cruz, Arie van Deursen: Code smells for machine learning applications. CAIN 2022: 217-228