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The Dark Side of Machine Learning Algorithms: How and Why They Can Leverage Bias, and What Can Be Done to Pursue Algorithmic Fairness

. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, стр. 3586--3587. (2020)

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Mariya Vasileva

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Другие публикации лиц с тем же именем

OutfitTransformer: Learning Outfit Representations for Fashion Recommendation., , , , , , и . WACV, стр. 3590-3598. IEEE, (2023)Why Do These Match? Explaining the Behavior of Image Similarity Models., , , , и . ECCV (11), том 12356 из Lecture Notes in Computer Science, стр. 652-669. Springer, (2020)Learning Type-Aware Embeddings for Fashion Compatibility., , , , , и . ECCV (16), том 11220 из Lecture Notes in Computer Science, стр. 405-421. Springer, (2018)Learning Similarity Conditions Without Explicit Supervision., , , и . ICCV, стр. 10372-10381. IEEE, (2019)Why do These Match? Explaining the Behavior of Image Similarity Models., , , , и . CoRR, (2019)Understanding the rich world of outfits: a study of fashion compatibility, latent style, and outfit behavior. University of Illinois Urbana-Champaign, USA, (2020)HandsOff: Labeled Dataset Generation With No Additional Human Annotations., , , и . CVPR, стр. 7991-8000. IEEE, (2023)OutfitTransformer: Outfit Representations for Fashion Recommendation., , , , , , и . CVPR Workshops, стр. 2262-2266. IEEE, (2022)The Dark Side of Machine Learning Algorithms: How and Why They Can Leverage Bias, and What Can Be Done to Pursue Algorithmic Fairness.. KDD, стр. 3586-3587. ACM, (2020)