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While learning these valuation functions over general distributions turns out to be hard, we present compact approximate representations and efficient learning algorithms for such functions over the uniform distribution.<\/jats:p>","DOI":"10.1145\/2692359.2692371","type":"journal-article","created":{"date-parts":[[2014,11,26]],"date-time":"2014-11-26T14:51:56Z","timestamp":1417013516000},"page":"50-53","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Structure and learning of valuation functions"],"prefix":"10.1145","volume":"12","author":[{"given":"Vitaly","family":"Feldman","sequence":"first","affiliation":[{"name":"IBM Almaden Research Center"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Vondr\u00e1k","sequence":"additional","affiliation":[{"name":"IBM Almaden Research Center"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2014,11,25]]},"reference":[{"key":"e_1_2_1_1_1","first-page":"4","article-title":"Learning valuation functions. 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