{"year":"2021","publication_status":"published","oa":1,"quality_controlled":"1","article_type":"original","day":"01","status":"public","citation":{"chicago":"Henzinger, Monika H, and Pan Peng. “Constant-Time Dynamic Weight Approximation for Minimum Spanning Forest.” Information and Computation. Elsevier, 2021. https://doi.org/10.1016/j.ic.2021.104805.","ama":"Henzinger MH, Peng P. Constant-time dynamic weight approximation for minimum spanning forest. Information and Computation. 2021;281(12). doi:10.1016/j.ic.2021.104805","short":"M.H. Henzinger, P. Peng, Information and Computation 281 (2021).","apa":"Henzinger, M. H., & Peng, P. (2021). Constant-time dynamic weight approximation for minimum spanning forest. Information and Computation. Elsevier. https://doi.org/10.1016/j.ic.2021.104805","ieee":"M. H. Henzinger and P. Peng, “Constant-time dynamic weight approximation for minimum spanning forest,” Information and Computation, vol. 281, no. 12. Elsevier, 2021.","ista":"Henzinger MH, Peng P. 2021. Constant-time dynamic weight approximation for minimum spanning forest. Information and Computation. 281(12), 104805.","mla":"Henzinger, Monika H., and Pan Peng. “Constant-Time Dynamic Weight Approximation for Minimum Spanning Forest.” Information and Computation, vol. 281, no. 12, 104805, Elsevier, 2021, doi:10.1016/j.ic.2021.104805."},"external_id":{"arxiv":["2011.00977"]},"publication":"Information and Computation","date_created":"2022-08-08T10:58:29Z","doi":"10.1016/j.ic.2021.104805","_id":"11756","intvolume":" 281","author":[{"orcid":"0000-0002-5008-6530","last_name":"Henzinger","first_name":"Monika H","full_name":"Henzinger, Monika H","id":"540c9bbd-f2de-11ec-812d-d04a5be85630"},{"last_name":"Peng","full_name":"Peng, Pan","first_name":"Pan"}],"publisher":"Elsevier","scopus_import":"1","date_updated":"2022-09-12T09:29:29Z","language":[{"iso":"eng"}],"abstract":[{"text":"We give two fully dynamic algorithms that maintain a (1 + ε)-approximation of the weight M of a minimum spanning forest (MSF) of an n-node graph G with edges weights in [1, W ], for any ε > 0. (1) Our deterministic algorithm takes O (W 2 log W /ε3) worst-case update time, which is O (1) if both W and ε are constants. (2) Our randomized (Monte-Carlo style) algorithm works with high probability and runs in worst-case O (log W /ε4) update time if W = O ((m∗)1/6/log2/3 n), where m∗ is the minimum number of edges in the graph throughout all the updates. It works even against an adaptive adversary. We complement our algorithmic results with two cell-probe lower bounds for dynamically maintaining an approximation of the weight of an MSF of a graph.","lang":"eng"}],"article_number":"104805","main_file_link":[{"url":"https://arxiv.org/abs/2011.00977","open_access":"1"}],"date_published":"2021-12-01T00:00:00Z","extern":"1","type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"12","month":"12","oa_version":"Preprint","volume":281,"article_processing_charge":"No","publication_identifier":{"issn":["0890-5401"]},"title":"Constant-time dynamic weight approximation for minimum spanning forest"}