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We present three new improvements to the state of the art: a barrier-aware line-search filter that cures blocked descent steps due to element barrier terms and so enables rapid progress; an energy proxy model that adaptively blends the Sobolev (inverse-Laplacian-processed) gradient and L-BFGS descent to gain the advantages of both, while avoiding L-BFGS's current limitations in distortion optimization tasks; and a characteristic gradient norm providing a robust and largely mesh- and energy-independent convergence criterion that avoids wrongful termination when algorithms temporarily slow their progress. Together these improvements form the basis for Blended Cured Quasi-Newton (BCQN), a new distortion optimization algorithm. Over a wide range of problems over all scales we show that BCQN is generally the fastest and most robust method available, making some previously intractable problems practical while offering up to an order of magnitude improvement in others.<\/jats:p>","DOI":"10.1145\/3197517.3201359","type":"journal-article","created":{"date-parts":[[2018,7,31]],"date-time":"2018-07-31T15:56:23Z","timestamp":1533052583000},"page":"1-14","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":57,"title":["Blended cured quasi-newton for distortion optimization"],"prefix":"10.1145","volume":"37","author":[{"given":"Yufeng","family":"Zhu","sequence":"first","affiliation":[{"name":"University of British Columbia &amp; Adobe Research"}]},{"given":"Rook","family":"Bridson","sequence":"additional","affiliation":[{"name":"Autodesk &amp; University of British Columbia"}]},{"given":"Danny M.","family":"Kaufman","sequence":"additional","affiliation":[{"name":"Adobe Research"}]}],"member":"320","published-online":{"date-parts":[[2018,7,30]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2766921"},{"key":"e_1_2_2_2_1","volume-title":"Conformal flattening by curvature prescription and metric scaling. 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