{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T20:52:10Z","timestamp":1765486330612},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>We propose the Graph Space Embedding (GSE), a technique that maps the input into a space where interactions are implicitly encoded, with little computations required. We provide theoretical results on an optimal regime for the GSE, namely a feasibility region for its parameters, and demonstrate the experimental relevance of our findings. Next, we introduce a strategy to gain insight on which interactions are responsible for the certain predictions, paving the way for a far more transparent model. In an empirical evaluation on a real-world clinical cohort containing patients with suspected coronary artery disease, the GSE achieves far better performance than traditional algorithms.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/451","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:46:05Z","timestamp":1564299965000},"page":"3253-3259","source":"Crossref","is-referenced-by-count":2,"title":["Graph Space Embedding"],"prefix":"10.24963","author":[{"given":"Jo\u00e3o","family":"Pereira","sequence":"first","affiliation":[{"name":"Amsterdam University Medical Center, The Netherlands"},{"name":"Horaizon BV, The Netherlands"}]},{"given":"Albert K.","family":"Groen","sequence":"additional","affiliation":[{"name":"Amsterdam University Medical Center, The Netherlands"}]},{"given":"Erik S. G.","family":"Stroes","sequence":"additional","affiliation":[{"name":"Amsterdam University Medical Center, The Netherlands"}]},{"given":"Evgeni","family":"Levin","sequence":"additional","affiliation":[{"name":"Amsterdam University Medical Center, The Netherlands"},{"name":"Horaizon BV, The Netherlands"}]}],"member":"10584","event":{"number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2019","name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","start":{"date-parts":[[2019,8,10]]},"theme":"Artificial Intelligence","location":"Macao, China","end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:49:23Z","timestamp":1564300163000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/451"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/451","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}