{"type":"ScholarlyArticle","title":"Machine Learning Approaches to Reduce Electrical Waste and Improve Power Grid Stability","authors":[{"name":"Mark Valovage","slug":"mark-valovage","given":"Mark","family":"Valovage","affiliation":"Computer Science and Engineering University of Minnesota , Minneapolis , MN"}],"abstract":"My research contributions are summarized as follows: In electricity disaggregation, I introduced the first label correction approach for supervised training samples. For unsupervised disaggregation, I introduced event detection that does not require parameter tuning and appliance discovery that makes no assumptions on appliance types. These improvements produce better accuracy, faster computation, and more scalability than any previously introduced method and can be applied to natural gas disaggregation, water disaggregation, and other source separation domains.  My current work challenges long-held assumptions in time series shapelets, a classification tool with applicability in electrical time series and dozens of additional domains.","doi":"10.24963/ijcai.2018/839","url":"https://ijcai.org/proceedings/2018/839","pdf":"https://ijcai.org/proceedings/2018/0839.pdf","markdown":"https://ijcai.org/proceedings/2018/839.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/839","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":839,"pages":{"first":5791,"last":5792},"keywords":["Machine Learning: Classification","Machine Learning: Time-series/Data Streams","Machine Learning: Data Mining","Machine Learning: Feature Selection/Construction"],"videos":[],"references":[{"position":1,"raw":"[Biswal et al., 2016] Milan Biswal, Yifan Hao, Phillip Chen, Suku- mar Brahma, Huiping Cao, and Phillip De Leon. Signal features for classification of power system disturbances using pmu data. In Power Systems Computation Conference (PSCC), pages 1-7. IEEE, 2016.","title":"Signal features for classification of power system disturbances using pmu data","authors":"Biswal","year":"2016","venue":"Power Systems Computation Conference (PSCC)","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Kolter et al., 2010] J Zico Kolter, Siddharth Batra, and Andrew Y Ng. Energy disaggregation via discriminative sparse coding. In NIPS, 2010.","title":"Energy disaggregation via discriminative sparse coding","authors":"Kolter","year":"2010","venue":"NIPS","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Patri et al., 2014] Om P Patri, Anand V Panangadan, Charalampos Chelmis, and Viktor K Prasanna. Extracting discriminative fea- tures for event-based electricity disaggregation. In Technologies for Sustainability (SusTech), pages 232-238. IEEE, 2014.","title":"Extracting discriminative features for event-based electricity disaggregation","authors":"Om P Patri, Charalampos Anand V Panangadan, Chelmis, Viktor, Prasanna","year":"2014","venue":"Technologies for Sustainability (SusTech)","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Valovage and Gini, 2016] Mark Valovage and Maria Gini. Auto- matic label correction and device prioritization in single house- hold electricity disaggregation. Int'l. Workshop on A.I. for Smart Grids and Smart Buildings, at AAAI, 2016.","title":"Automatic label correction and device prioritization in single household electricity disaggregation","authors":"Mark Valovage, Maria Gini","year":"2016","venue":"Int'l. Workshop on A.I. for Smart Grids and Smart Buildings","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Valovage and Gini, 2017] Mark Valovage and Maria Gini. Label correction and event detection for electricity disaggregation. In Proc. of the 16th Conf. on Autonomous Agents and MultiAgent Systems, pages 990-998. IFAAMAS, 2017.","title":"Label correction and event detection for electricity disaggregation","authors":"Mark Valovage, Maria Gini","year":"2017","venue":"Proc. of the 16th Conf. on Autonomous Agents and MultiAgent Systems","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Valovage et al., 2018] Mark Valovage, Akshay Shekhawat, and Maria Gini. Model-free iterative temporal appliance discovery for unsupervised electricity disaggregation. In Proc. AAAI, 2018.","title":"Model-free iterative temporal appliance discovery for unsupervised electricity disaggregation","authors":"Mark Valovage, Akshay Shekhawat, Maria Gini","year":"2018","venue":"Proc. AAAI","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}