{"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/robust-and-efficient-transfer-learning-with","title":"Robust and Efficient Transfer Learning with Hidden-Parameter Markov Decision Processes","arxiv_id":"1706.06544","date":"2017-06-20","proceeding":null,"authors":["Taylor Killian","Samuel Daulton","George Konidaris","Finale Doshi-Velez"],"abstract":"We introduce a new formulation of the Hidden Parameter Markov Decision\nProcess (HiP-MDP), a framework for modeling families of related tasks using\nlow-dimensional latent embeddings. Our new framework correctly models the joint\nuncertainty in the latent parameters and the state space. We also replace the\noriginal Gaussian Process-based model with a Bayesian Neural Network, enabling\nmore scalable inference. Thus, we expand the scope of the HiP-MDP to\napplications with higher dimensions and more complex dynamics.","url_abs":"http://arxiv.org/abs/1706.06544v3","url_pdf":"http://arxiv.org/pdf/1706.06544v3.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":"robust-and-efficient-transfer-learning-with","repo_url":"https://github.com/dtak/hip-mdp-public","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"transfer-learning","task_name":"Transfer Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1706.06544","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}