1 to 4 of 4 Results
Jan 3, 2023
Barbato, Michele; Ceselli, Alberto, 2022, "Technical Report of "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm"", https://doi.org/10.13130/RD_UNIMI/UA8PFI, UNIMI Dataverse, V3
Technical Report of "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm". Broad experimental campaign. Due to a new implementation, the reported results are outdated. The new results can be found on: https://doi.org/10.13130/RD_UNIMI/L... |
Oct 26, 2022
Barbato, Michele; Ceselli, Alberto, 2022, "Replication Data for: "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm"", https://doi.org/10.13130/RD_UNIMI/1MZNNS, UNIMI Dataverse, V1, UNF:6:PWiIzt/vPLfrW/Rq52qghw== [fileUNF]
Training and test instances used in the work "Mathematical Programming for Simultaneous Feature Selection and Outlier Detection under l1 Norm". Several new instances are available at the related datatset available here: https://doi.org/10.13130/RD_UNIMI/LZA4F8 |
Oct 12, 2022
Ceselli, Alberto; Basso, Saverio, 2022, "Replication data for 'A data driven Dantzig–Wolfe decomposition framework'", https://doi.org/10.13130/RD_UNIMI/T99WYI, UNIMI Dataverse, V1
The dataset contains a set of about 31000 random decompositions of MIPLib instances, together with (a) an evaluation of a set of 121 features over them (b) bound and time scores, obtained through optimization runs. Their detailed structure is described in the paper: S. Basso, A.... |
Jan 11, 2022
Ceselli, Alberto; Casazza, Marco, 2022, "Replication data for "Exact Algorithms for Maximum Lifetime Data-Gathering Tree in Wireless Sensor Networks"", https://doi.org/10.13130/RD_UNIMI/VHW2QV, UNIMI Dataverse, V1, UNF:6:U/L+h6e36wYpccCRTD5/Rg== [fileUNF]
Dataset of instances used in the paper "Exact algorithms for Maximum Lifetime Data Gathering Tree in Wireless Sensors Networks". The repository contains two folders (CCD and ZTD) corresponding to the instances used in the paper. Their full description is given in two README files... |