{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T13:25:52Z","timestamp":1762867552822},"reference-count":29,"publisher":"Association for Computing Machinery (ACM)","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>\n            Recovering a time sequence of events from multiple aggregated and possibly overlapping reports is a major challenge in historical data fusion. The goal is to reconstruct a higher resolution event sequence from a mixture of lower resolution samples as accurately as possible. For example, we may aim to disaggregate overlapping monthly counts of people infected with measles into weekly counts. In this paper, we propose a novel data disaggregation method, called H\n            <jats:sc>ome<\/jats:sc>\n            R\n            <jats:sc>un<\/jats:sc>\n            , that exploits an alternative representation of the sequence and finds the spectrum of the target sequence. More specifically, we formulate the problem as so-called\n            <jats:italic>basis pursuit<\/jats:italic>\n            using the Discrete Cosine Transform (DCT) as a sparsifying dictionary\n            <jats:italic>and<\/jats:italic>\n            impose non-negativity and smoothness constraints. H\n            <jats:sc>ome<\/jats:sc>\n            R\n            <jats:sc>un<\/jats:sc>\n            utilizes the energy compaction feature of the DCT by finding the sparsest spectral representation of the target sequence that contains the largest (most important) coefficients. We leverage the\n            <jats:italic>Alternating Direction Method of Multipliers<\/jats:italic>\n            to solve the resulting optimization problem with scalable and memory efficient steps. Experiments using real epidemiological data show that our method considerably outperforms the state-of-the-art techniques, especially when the DCT of the sequence has a high degree of energy compaction.\n          <\/jats:p>","DOI":"10.14778\/3236187.3236201","type":"journal-article","created":{"date-parts":[[2018,9,10]],"date-time":"2018-09-10T12:12:28Z","timestamp":1536581548000},"page":"1496-1508","source":"Crossref","is-referenced-by-count":7,"title":["Homerun"],"prefix":"10.14778","volume":"11","author":[{"given":"Faisal M.","family":"Almutairi","sequence":"first","affiliation":[{"name":"University of Minnesota"}]},{"given":"Fan","family":"Yang","sequence":"additional","affiliation":[{"name":"University of Pittsburgh"}]},{"given":"Hyun Ah","family":"Song","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University"}]},{"given":"Christos","family":"Faloutsos","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University"}]},{"given":"Nicholas","family":"Sidiropoulos","sequence":"additional","affiliation":[{"name":"University of Virginia"}]},{"given":"Vladimir","family":"Zadorozhny","sequence":"additional","affiliation":[{"name":"University of Pittsburgh"}]}],"member":"320","published-online":{"date-parts":[[2018,7]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/T-C.1974.223784"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-3975(94)00254-G"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1456650.1456651"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"e_1_2_1_5_1","first-page":"1433","volume-title":"Proceedings of the international congress of mathematicians","volume":"3","author":"Cand\u00e8s E. 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