{"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/common-representation-learning-using-step","title":"Common Representation Learning Using Step-based Correlation Multi-Modal CNN","arxiv_id":"1711.00003","date":"2017-10-31","proceeding":null,"authors":["Gaurav Bhatt","Piyush Jha","Balasubramanian Raman"],"abstract":"Deep learning techniques have been successfully used in learning a common\nrepresentation for multi-view data, wherein the different modalities are\nprojected onto a common subspace. In a broader perspective, the techniques used\nto investigate common representation learning falls under the categories of\ncanonical correlation-based approaches and autoencoder based approaches. In\nthis paper, we investigate the performance of deep autoencoder based methods on\nmulti-view data. We propose a novel step-based correlation multi-modal CNN\n(CorrMCNN) which reconstructs one view of the data given the other while\nincreasing the interaction between the representations at each hidden layer or\nevery intermediate step. Finally, we evaluate the performance of the proposed\nmodel on two benchmark datasets - MNIST and XRMB. Through extensive\nexperiments, we find that the proposed model achieves better performance than\nthe current state-of-the-art techniques on joint common representation learning\nand transfer learning tasks.","url_abs":"http://arxiv.org/abs/1711.00003v1","url_pdf":"http://arxiv.org/pdf/1711.00003v1.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":"common-representation-learning-using-step","repo_url":"https://github.com/rishabh26malik/Common-Representation-Learning","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"representation-learning","task_name":"Representation Learning"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}