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

Dadush, D.N, Hojny, C, Huiberts, S, & Weltge, S. (2023). A simple method for convex optimization in the oracle model. Mathematical Programming Series B. doi:10.1007/s10107-023-02005-8
Borst, S.J, Dadush, D.N, Huiberts, S, & Kashaev, D. (2023). A nearly optimal randomized algorithm for explorable heap selection. In Proceedings of the 24th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2023 (pp. 29–43). doi:10.1007/978-3-031-32726-1_3
Dadush, D.N, Eisenbrand, F, & Rothvoss, T. (2023). From approximate to exact integer programming. In Proceedings of the 24th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2023 (pp. 100–114). doi:10.1007/978-3-031-32726-1_8
Dadush, D.N, Léonard, A. (Arthur), Rohwedder, L, & Verschae, J. (2023). Optimizing low dimensional functions over the integers. In Proceedings of the 24th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2023 (pp. 115–126). doi:10.1007/978-3-031-32726-1_9
Dadush, D.N, Huiberts, S, Natura, B, & Végh, L.A. (2023). A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. Mathematical Programming. doi:10.1007/s10107-023-01956-2
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

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)