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Comparing Consumption Forecast Models for Demand Response Optimization in a Microgrid, , and . (2013)Under Review by Transactions on Knowledge and Data Engineering (TKDE) IF 1.657, CORE A.Using Roget's Thesaurus for Fine-grained Emotion Recognition., and . IJCNLP, page 312-318. The Association for Computer Linguistics, (2008)Prediction Models for Dynamic Demand Response: Requirements, Challenges, and Insights, , , , , and . IEEE International Conference on Smart Grid Communications (SmartGridComm), page 1--6. (2015)Cloud-based Software Platform for Data-Driven Smart Grid Management, , , , , , and . Computing in Science and Engineering, (2013)IF 1.422, CORE C.Improving Energy Use Forecast for Campus Micro-grids using Indirect Indicators, , and . International Workshop on Domain Driven Data Mining (DDDM), page 389--397. (2011)Scalable, Secure Energy Information Management for DR Analysis, , , , , , , and . Southern California Smart Grid Research Symposium (SoCalSGS), University of Southern California, (October 2010)Poster.Challenge: On Online Time Series Clustering for Demand Response: Optic - A Theory to Break the 'Curse of Dimensionality'., , , , , and . e-Energy, page 95-100. ACM, (2015)Toward data-driven demand-response optimization in a campus microgrid., , , , , and . BuildSys@SenSys, page 41-42. ACM, (2011)Identifying Expressions of Emotion in Text., and . TSD, volume 4629 of Lecture Notes in Computer Science, page 196-205. Springer, (2007)Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids, , , , , , , , , and 1 other author(s). IEEE International Scalable Computing Challenge (SCALE), page 1--4. (2012)SCALE Challenge Winner.