2026-09-20T00:43:01Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/101223 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Embargo set by: Seth Robbins for item 107307 Lift date: 2020-09-04T20:37:00Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Embargo set by: Seth Robbins for item 107307 Lift date: 2020-09-04T20:42:08Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only Restriction Lifted for Item 107307 on 2020-09-05T09:15:26Z. application/pdf en Koyejo, Oluwasanmi Zhu, Yizhi 2018-09-04T20:36:54Z 2018-09-04T20:36:54Z 2020-09-05T09:15:26Z 2018-04-26 2018-05 Estimating the dynamic connectivity structure among a system of entities has garnered much attention in recent years. While usual methods are designed to take advantage of temporal consistency to overcome noise, they conflict with the detectability of anomalies. We propose Clustered Fused Graphical Lasso (CFGL), a method using precomputed clustering information to improve the signal detectability as compared to typical Fused Graphical Lasso methods. We evaluate our method in both simulated and real-world datasets and conclude that, in many cases, CFGL can significantly improve the sensitivity to signals without a significant negative effect on the temporal consistency Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-05-01 The student, Yizhi Zhu, accepted the attached license on 2018-04-26 at 11:52. The student, Yizhi Zhu, submitted this Thesis for approval on 2018-04-26 at 12:03. This Thesis was approved for publication on 2018-04-26 at 15:24. DSpace SAF Submission Ingestion Package generated from Vireo submission #12457 on 2018-08-31 at 17:21:27 Made available in DSpace on 2018-09-04T20:36:54Z (GMT). No. of bitstreams: 2 ZHU-THESIS-2018.pdf: 1384166 bytes, checksum: 806f68a067204b1e2dfb3fd575e94f26 (MD5) LICENSE.txt: 4206 bytes, checksum: 798bd7aa3fcde38630f40d35c95ec628 (MD5) Previous issue date: 2018-04-26 http://hdl.handle.net/2142/101223 Copyright 2018 Yizhi Zhu Network Inference Time Series Graphical Lasso Network inference via clustered fused graphical lasso text text Computer Science Computer Science University of Illinois at Urbana-Champaign Thesis M.S.