{"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/supervised-deep-sparse-coding-networks","title":"Supervised Deep Sparse Coding Networks","arxiv_id":"1701.08349","date":"2017-01-29","proceeding":null,"authors":["Xiaoxia Sun","Nasser M. Nasrabadi","Trac. D. Tran"],"abstract":"In this paper, we describe the deep sparse coding network (SCN), a novel deep\nnetwork that encodes intermediate representations with nonnegative sparse\ncoding. The SCN is built upon a number of cascading bottleneck modules, where\neach module consists of two sparse coding layers with relatively wide and slim\ndictionaries that are specialized to produce high dimensional discriminative\nfeatures and low dimensional representations for clustering, respectively.\nDuring training, both the dictionaries and regularization parameters are\noptimized with an end-to-end supervised learning algorithm based on multilevel\noptimization. Effectiveness of an SCN with seven bottleneck modules is verified\non several popular benchmark datasets. Remarkably, with few parameters to\nlearn, our SCN achieves 5.81% and 19.93% classification error rate on CIFAR-10\nand CIFAR-100, respectively.","url_abs":"http://arxiv.org/abs/1701.08349v3","url_pdf":"http://arxiv.org/pdf/1701.08349v3.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":"supervised-deep-sparse-coding-networks","repo_url":"https://github.com/XiaoxiaSun/supervised-deep-sparse-coding-networks","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}