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We also devise an online algorithm to compute such output distributions, which employs a suite of optimizations to improve accuracy and performance. Our evaluation using both real-world and synthetic functions shows that our proposed GP approach can outperform the state-of-the-art sampling approach with up to two orders of magnitude improvement for a variety of UDFs.<\/jats:p>","DOI":"10.14778\/2536336.2536347","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"469-480","source":"Crossref","is-referenced-by-count":1,"title":["Supporting user-defined functions on uncertain data"],"prefix":"10.14778","volume":"6","author":[{"given":"Thanh T. 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