{"url":"/dataset/f-celeba-10-tasks","name":"F-CelebA (10 tasks)","full_name":"Federated-CelebA (10 tasks)","description_markdown":"F-CelebA - This dataset is adapted from federated learning. Federated learning\r\nis an emerging machine learning paradigm with an emphasis on data privacy. The idea is to train\r\nthrough model aggregation rather than conventional data aggregation and keep local data staying\r\non the local device. This dataset naturally consists of similar tasks and each of the 10 tasks contains images of a celebrity labeled by whether he/she is smiling or not. More detailed please check page https://github.com/ZixuanKe/CAT","description_withheld":null,"homepage":"https://github.com/ZixuanKe/CAT","introduced_date":"2021-12-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/continual-learning-of-a-mixed-sequence-of-1","title":"Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks","first_author":"Zixuan Ke","url":null},"license":null,"modalities":[],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Continual Learning","url":"/task/continual-learning","datasets_with_task":"/datasets/task/continual-learning"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["F-CelebA (10 tasks)"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/continual-learning-on-f-celeba-10-tasks","task":"Continual Learning","dataset_variant":"F-CelebA (10 tasks)","rows":7,"metrics":["Acc"],"first_row_in_archive_order":{"model":"CAT (CNN backbone)","paper":"/paper/continual-learning-of-a-mixed-sequence-of-1","metrics":{"Acc":"0.7564"},"code_links":[{"title":"zixuanke/pycontinual","url":"https://github.com/zixuanke/pycontinual"},{"title":"ZixuanKe/CAT","url":"https://github.com/ZixuanKe/CAT"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/continual-learning-of-a-mixed-sequence-of-1","title":"Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks","date":"2021-12-18","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/random-path-selection-for-continual-learning","title":"Random Path Selection for Continual Learning","date":"2019-12-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/190600695","title":"Continual learning with hypernetworks","date":"2019-06-03","rows_on_this_dataset":1,"code_links":9,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/overcoming-catastrophic-forgetting-with-hard","title":"Overcoming catastrophic forgetting with hard attention to the task","date":"2018-01-04","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/pathnet-evolution-channels-gradient-descent","title":"PathNet: Evolution Channels Gradient Descent in Super Neural Networks","date":"2017-01-30","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/overcoming-catastrophic-forgetting-in-neural","title":"Overcoming catastrophic forgetting in neural networks","date":"2016-12-02","rows_on_this_dataset":1,"code_links":29,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":22,"samples_ran":14,"samples_unverified":8,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":25,"samples_ran":15,"samples_unverified":10,"pointer_only_for_licence":5,"papers_with_no_sample_that_ran":1,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}