{"url":"/method/batch-nuclear-norm-maximization","slug":"batch-nuclear-norm-maximization","name":"Batch Nuclear-norm Maximization","full_name":"Batch Nuclear-norm Maximization","full_name_withheld":false,"description_markdown":"**Batch Nuclear-norm Maximization** is an approach for aiding classification in label insufficient situations. It involves maximizing the nuclear-norm of the batch output matrix. The nuclear-norm of a matrix is an upper bound of the Frobenius-norm of the matrix. Maximizing nuclear-norm ensures large Frobenius-norm of the batch matrix, which leads to increased discriminability. The nuclear-norm of the batch matrix is also a convex approximation of the matrix rank, which refers to the prediction diversity.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations","paper":"/paper/towards-discriminability-and-diversity-batch","first_author":"Shuhao Cui","n_authors":6,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/towards-discriminability-and-diversity-batch"},"source":{"url":"https://arxiv.org/abs/2003.12237v1","title":"Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Regularization","url":"/methods/category/regularization","pwc_aliases":[]}],"n_papers_tagged":3,"archive_num_papers":3,"papers_newest_first":[{"paper":"/paper/fast-batch-nuclear-norm-maximization-and","title":"Fast Batch Nuclear-norm Maximization and Minimization for Robust Domain Adaptation","date":"2021-07-13","arxiv_id":"2107.06154","n_code_links":1,"syntology":{"ran":0,"of":1,"unverified":1,"pointer_only":1}},{"paper":"/paper/learning-invariant-representation-with","title":"Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis Transfer","date":"2021-07-07","arxiv_id":"2107.03008","n_code_links":1,"syntology":null},{"paper":"/paper/towards-discriminability-and-diversity-batch","title":"Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations","date":"2020-03-27","arxiv_id":"2003.12237","n_code_links":2,"syntology":{"ran":2,"of":4,"unverified":2,"pointer_only":0}}],"papers_shown":3,"tasks":[{"task":"/task/diversity","name":"Diversity","papers":3},{"task":"/task/domain-adaptation","name":"Domain Adaptation","papers":3},{"task":"/task/prediction","name":"Prediction","papers":1},{"task":"/task/semi-supervised-domain-adaptation","name":"Semi-supervised Domain Adaptation","papers":1}],"tasks_shown":4,"n_tasks":4,"usage_by_year":[{"year":"2020","papers":1},{"year":"2021","papers":2}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/batch-nuclear-norm-maximization"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}