{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/arcade-a-rapid-continual-anomaly-detector","title":"ARCADe: A Rapid Continual Anomaly Detector","arxiv_id":"2008.04042","date":"2020-08-10","proceeding":null,"authors":["Ahmed Frikha","Denis Krompaß","Volker Tresp"],"abstract":"Although continual learning and anomaly detection have separately been well-studied in previous works, their intersection remains rather unexplored. The present work addresses a learning scenario where a model has to incrementally learn a sequence of anomaly detection tasks, i.e. tasks from which only examples from the normal (majority) class are available for training. We define this novel learning problem of continual anomaly detection (CAD) and formulate it as a meta-learning problem. Moreover, we propose A Rapid Continual Anomaly Detector (ARCADe), an approach to train neural networks to be robust against the major challenges of this new learning problem, namely catastrophic forgetting and overfitting to the majority class. The results of our experiments on three datasets show that, in the CAD problem setting, ARCADe substantially outperforms baselines from the continual learning and anomaly detection literature. Finally, we provide deeper insights into the learning strategy yielded by the proposed meta-learning algorithm.","url_abs":"https://arxiv.org/abs/2008.04042v2","url_pdf":"https://arxiv.org/pdf/2008.04042v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"arcade-a-rapid-continual-anomaly-detector","repo_url":"https://github.com/AhmedFrikha/ARCADe-A-Rapid-Continual-Anomaly-Detector","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"anomaly-detection","task_name":"Anomaly Detection"},{"task_slug":"continual-learning","task_name":"Continual Learning"},{"task_slug":"meta-learning","task_name":"Meta-Learning"},{"task_slug":"one-class-classifier","task_name":"One-class classifier"},{"task_slug":"continual-anomaly-detection","task_name":"continual anomaly detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2008.04042","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.04042"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/AhmedFrikha/ARCADe-A-Rapid-Continual-Anomaly-Detector","reach":null}],"summary":{"ran_draft_wrong":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"c09ce24d7c70b40d","entry":"extract_args_from_json","repo":"AhmedFrikha/ARCADe-A-Rapid-Continual-Anomaly-Detector","repo_kind":"official","path":"arcade_main.py","file_url":"https://github.com/AhmedFrikha/ARCADe-A-Rapid-Continual-Anomaly-Detector/blob/HEAD/arcade_main.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"c09ce24d7c70b40d"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}