Daniel Dadush

Full Name

Dr. D.N. Dadush

Email

D.N.Dadush@cwi.nl

Phone

+31 20 592 4210

Room

M234

Department(s)

Networks and Optimization

Function(s)

Scientific Staff Member, Group leader

Homepage

https://homepages.cwi.nl/~dadush/

Daniel Dadush

Allamigeon, X, Dadush, D.N, Loho, G, Natura, B, & Végh, L.A. (2022). Interior point methods are not worse than Simplex. In Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS (pp. 267–277). doi:10.1109/FOCS54457.2022.00032
Bonnet, G.F.Y, Dadush, D.N, Grupel, U, Huiberts, S, & Livshyts, G. (2022). Asymptotic Bounds on the Combinatorial Diameter of Random Polytopes. In Leibniz International Proceedings in Informatics (pp. 18:1–18:15). doi:10.4230/LIPIcs.SoCG.2022.18
Dadush, D.N, Koh, Z.K, Natura, B, & Végh, L.A. (2021). An accelerated Newton–Dinkelbach method and its application to two variables per inequality systems. In Annual European Symposium on Algorithms (pp. 36.1–36.15). doi:10.4230/LIPIcs.ESA.2021.36
Dadush, D.N, Végh, L.A, & Zambelli, G. (2021). Geometric rescaling algorithms for submodular function minimization. Mathematics of Operations Research, 46(3), 1081–1108. doi:10.1287/MOOR.2020.1064
Borst, S.J, Dadush, D.N, Huiberts, S, & Tiwari, S.S.K. (2021). On the integrality gap of binary integer programs with Gaussian data. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 427–442). doi:10.1007/978-3-030-73879-2_30
Borst, S.J, Dadush, D.N, Olver, N.K, & Sinha, M. (2021). Majorizing measures for the optimizer. In 12th Innovations in Theoretical Computer Science Conference, ITCS 2021 (pp. 73:1–73:20). doi:10.4230/LIPIcs.ITCS.2021.73
Dadush, D.N, & Huiberts, S. (2020). A friendly smoothed analysis of the simplex method. SIAM Journal on Computing, 49(5). doi:10.1137/18M1197205
Dadush, D.N, & Huiberts, S. (2020). Smoothed analysis of the simplex method. In T Roughgarden (Ed.), Beyond the Worst-Case Analysis of Algorithms. Cambridge University Press.
Dadush, D.N, & Tiwari, S.S.K. (2020). On the complexity of branching proofs. In 35th Computational Complexity Conference, CCC 2020 (pp. 34:1–34:35). doi:10.4230/LIPIcs.CCC.2020.34
Dadush, D.N, Huiberts, S, Natura, B, & Végh, L.A. (2020). A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. In Proceedings of the Annual ACM Symposium on Theory of Computing (pp. 761–774). doi:10.1145/3357713.3384326

Van Dantzig Prize (2020)
Best Paper Award at CCC'20 (2020)
Towards a Quantitative Theory of Integer Programming (2018)
Tucker Prize (2015)

Board Member: Lorentz Center: Mathematics Scientific Advisory Board
Editor: Associate Editor: Mathematics of Operations Research

Veni Innovational Research Grant NWO (2015)

Towards a Quantitative Theory of Integer Programming (QIP)