diff --git a/README.md b/README.md index abb3912b28b1ad4fa322c92ef5b45c61561ae127..5e55d21822c425911d4bfda66bb1a47ffd986a68 100644 --- a/README.md +++ b/README.md @@ -12,25 +12,25 @@ The code implementing the AiGAS-dEVL approach described above is currently being - Sample at time 1: Feature1, Feature2, ... FeatureN, TrueLabel - Sample at time 2: Feature1, Feature2, ... FeatureN, TrueLabel -... +- ... - Sample at time Ts: Feature1, Feature2, ... FeatureN, TrueLabel, PredictedLabel - Sample at time Ts+1: Feature1, Feature2, ... FeatureN, TrueLabel, PredictedLabel - Sample at time Ts+2: Feature1, Feature2, ... FeatureN, TrueLabel, PredictedLabel -... +- ... For more information, please contact the corresponding author (Maria Arostegi, maria.arostegi@tecnalia.com). ## Please cite this work as: -@misc{arostegi2024, - title={{AiGAS-dEVL}: An Adaptive Incremental Neural Gas Model for Drifting Data Streams under Extreme Verification Latency}, - author={Maria Arostegi and Miren Nekane Bilbao and Jesus L. Lobo and Javier Del Ser}, - year={2024}, - eprint={waiting for ArXiV acceptance}, - archivePrefix={arXiv}, - primaryClass={cs.AI}, - url={https://arxiv.org}, -} +> @misc{arostegi2024, +> title={{AiGAS-dEVL}: An Adaptive Incremental Neural Gas Model for Drifting Data Streams under Extreme Verification Latency}, +> author={Maria Arostegi and Miren Nekane Bilbao and Jesus L. Lobo and Javier Del Ser}, +> year={2024}, +> eprint={waiting for ArXiV acceptance}, +> archivePrefix={arXiv}, +> primaryClass={cs.AI}, +> url={https://arxiv.org}, +>}