{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T17:48:26Z","timestamp":1764784106589},"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":[[2018,7]]},"abstract":"<jats:p>We present a novel framework for augmenting data sets for\n\nmachine learning based on counterexamples. Counterexamples\n\nare misclassified examples that have \n\nimportant properties for retraining and improving the model.\n\nKey components of our framework include a \\textit{counterexample generator},\n\nwhich produces data items that are misclassified by the model and\n\nerror tables, a novel data\n\nstructure that stores information pertaining to misclassifications.\n\nError tables can be used to explain the model's\n\nvulnerabilities and are used to efficiently generate counterexamples for augmentation.\n\nWe show the efficacy of the proposed framework by comparing it\n\nto classical augmentation techniques on a case study of object detection in autonomous\n\ndriving based on deep neural networks.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/286","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"2071-2078","source":"Crossref","is-referenced-by-count":34,"title":["Counterexample-Guided Data Augmentation"],"prefix":"10.24963","author":[{"given":"Tommaso","family":"Dreossi","sequence":"first","affiliation":[{"name":"University of California, Berkeley"}]},{"given":"Shromona","family":"Ghosh","sequence":"additional","affiliation":[{"name":"University of California, Berkeley"}]},{"given":"Xiangyu","family":"Yue","sequence":"additional","affiliation":[{"name":"University of California, Berkeley"}]},{"given":"Kurt","family":"Keutzer","sequence":"additional","affiliation":[{"name":"University of California, Berkeley"}]},{"given":"Alberto","family":"Sangiovanni-Vincentelli","sequence":"additional","affiliation":[{"name":"University of California, Berkeley"}]},{"given":"Sanjit A.","family":"Seshia","sequence":"additional","affiliation":[{"name":"University of California, Berkeley"}]}],"member":"10584","event":{"number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2018","name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","start":{"date-parts":[[2018,7,13]]},"theme":"Artificial Intelligence","location":"Stockholm, Sweden","end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:51:30Z","timestamp":1530755490000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/286"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/286","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}