Towards a Quantitative Theory of Integer Programming

Informazioni relative al progetto

QIP

ID dell’accordo di sovvenzione: 805241

DOI

10.3030/805241

Progetto chiuso

Data della firma CE 10 Settembre 2018

Data di avvio 1 Gennaio 2019

Data di completamento 31 Dicembre 2024

Finanziato da

• EXCELLENT SCIENCE - European Research Council (ERC)

Costo totale

€ 1 500 000,00

Contributo UE

€ 1 500 000,00

Coordinato da

STICHTING NEDERLANDSE WETENSCHAPPELIJK ONDERZOEK INSTITUTEN
Netherlands

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Pubblicazioni

Book chapters (8)

On Circuit Diameter Bounds via Circuit Imbalances

Autori: Daniel Dadush, Zhuan Khye Koh, Bento Natura, László A. Végh
Pubblicato in: Lecture Notes in Computer Science, Integer Programming and Combinatorial Optimization, 2022, Pagina/e 140-153
Editore: Springer International Publishing
DOI: 10.1007/978-3-031-06901-7_11

On finding exact solutions of linear programs in the oracle model

Autori: Daniel Dadush, László A. Végh, Giacomo Zambelli
Pubblicato in: Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2022, Pagina/e 2700-2722
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/1.9781611977073.106

Strongly Polynomial Frame Scaling to High Precision

Autori: Daniel Dadush, Akshay Ramachandran
Pubblicato in: Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2024, Pagina/e 962-981
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/1.9781611977912.36

Optimizing Low Dimensional Functions over the Integers

Autori: Daniel Dadush, Arthur Léonard, Lars Rohwedder, José Verschae
Pubblicato in: Lecture Notes in Computer Science, Integer Programming and Combinatorial Optimization, 2023, Pagina/e 115-126
Editore: Springer International Publishing
DOI: 10.1007/978-3-031-32726-1_9

On the Integrality Gap of Binary Integer Programs with Gaussian Data

Autori: Sander Borst, Daniel Dadush, Sophie Huiberts, Samarth Tiwari
Pubblicato in: Integer Programming and Combinatorial Optimization - 22nd International Conference, IPCO 2021, Atlanta, GA, USA, May 19–21, 2021, Proceedings, Numero 12707, 2021, Pagina/e 427-442, ISBN 978-3-030-73878-5
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-73879-2_30

A Simple Method for Convex Optimization in the Oracle Model

Autori: Daniel Dadush, Christopher Hojny, Sophie Huiberts, Stefan Weltge
Pubblicato in: Lecture Notes in Computer Science, Integer Programming and Combinatorial Optimization, 2022, Pagina/e 154-167
Editore: Springer International Publishing
DOI: 10.1007/978-3-031-06901-7_12

Smoothed Analysis of the Simplex Method

Autori: Daniel Dadush, Sophie Huiberts
Pubblicato in: Beyond the Worst-Case Analysis of Algorithms, 2022, Pagina/e 309-333
Editore: Cambridge University Press
DOI: 10.1017/9781108637435.019

A Nearly Optimal Randomized Algorithm for Explorable Heap Selection

Autori: Sander Borst, Daniel Dadush, Sophie Huiberts, Danish Kashaev
Pubblicato in: Lecture Notes in Computer Science, Integer Programming and Combinatorial Optimization, 2023, Pagina/e 29-43
Editore: Springer International Publishing
DOI: 10.1007/978-3-031-32726-1_3

Conference proceedings (13)

A Strongly Polynomial Algorithm for Linear Programs with At Most Two Nonzero Entries per Row or Column

Autori: Daniel Dadush, Zhuan Khye Koh, Bento Natura, Neil Olver, László A. Végh
Pubblicato in: Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 2024, Pagina/e 1561-1572
Editore: ACM
DOI: 10.1145/3618260.3649764

An Accelerated Newton-Dinkelbach Method and Its Application to Two Variables per Inequality Systems

Autori: Daniel Dadush, Zhuan Khye Koh, Bento Natura, and László A. Végh
Pubblicato in: Proceedings of the 29th Annual European Symposium on Algorithms (ESA 2021), 2021, Pagina/e 1-15
Editore: Leibniz International Proceedings in Informatics (LIPIcs)
DOI: 10.4230/lipics.esa.2021.36

A new framework for matrix discrepancy: partial coloring bounds via mirror descent

Autori: Daniel Dadush, Haotian Jiang, Victor Reis
Pubblicato in: STOC 2022: Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing, 2022
Editore: ACM
DOI: 10.1145/3519935.3519967

Interior point methods are not worse than Simplex

Autori: Xavier Allamigeon; Daniel Dadush; Georg Loho; Bento Natura; Laszlo A. Vegh
Pubblicato in: IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS), 2022
Editore: IEEE
DOI: 10.1109/focs54457.2022.00032

From Approximate to Exact Integer Programming

Autori: Dadush, Daniel; Eisenbrand, Friedrich; Rothvoss, Thomas
Pubblicato in: Integer Programming and Combinatorial Optimization, 2023
Editore: Springer
DOI: 10.1007/978-3-031-32726-1_8

On the complexity of branching proofs

Autori: Daniel Dadush, Samarth Tiwari
Pubblicato in: 35th Computational Complexity Conference (CCC 2020), 2020, Pagina/e 1-35
Editore: "Schloss Dagstuhl--Leibniz-Zentrum f{\""u}r Informatik"
DOI: 10.4230/lipics.ccc.2020.34

A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix

Autori: Daniel Dadush, Sophie Huiberts, Bento Natura, László A. Végh
Pubblicato in: Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020, Pagina/e 761-774, ISBN 9781-450369794
Editore: ACM
DOI: 10.1145/3357713.3384326

Integrality Gaps for Random Integer Programs via Discrepancy

Autori: Sander Borst, Daniel Dadush, Dan Mikulincer
Pubblicato in: Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2023, Pagina/e 1692-1733
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/1.9781611977554.ch65

Revisiting Tardos's Framework for Linear Programming: Faster Exact Solutions using Approximate Solvers

Autori: Daniel Dadush, Bento Natura, Laszlo A. Vegh
Pubblicato in: 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS), 2020, Pagina/e 931-942, ISBN 978-1-7281-9621-3
Editore: IEEE
DOI: 10.1109/focs46700.2020.00091

Interior point methods are not worse than Simplex

Autori: Xavier Allamigeon, Daniel Dadush, Georg Loho, Bento Natura, Laszlo A. Vegh
Pubblicato in: 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS), 2024, Pagina/e 267-277
Editore: IEEE
DOI: 10.1109/focs54457.2022.00032

Majorizing Measures for the Optimizer

Autori: Sander Borst, Daniel Dadush, Neil Olver, Makrand Sinha
Pubblicato in: 12th Innovations in Theoretical Computer Science Conference (ITCS 2021), 2021, Pagina/e 20
Editore: Leibniz International Proceedings in Informatics (LIPIcs)
DOI: 10.4230/lipics.itcs.2021.73

Majorizing measures for the optimizer

Autori: Borst, Sander; Dadush, Daniel; Olver, Neil; Sinha, Makrand
Pubblicato in: Proceedings of the 13th Conference on Innovations in Theoretical Computer Science (ITCS), 2021
Editore: "Schloss Dagstuhl--Leibniz-Zentrum f{\""u}r Informatik"
DOI: 10.4230/lipics.itcs.2021.73

Asymptotic Bounds on the Combinatorial Diameter of Random Polytopes

Autori: Bonnet, Gilles; Dadush, Daniel; Grupel, Uri; Huiberts, Sophie; Livshyts, Galyna
Pubblicato in: 38th International Symposium on Computational Geometry (SoCG 2022), 2022, Pagina/e 1-15
Editore: Leibniz International Proceedings in Informatics (LIPIcs)
DOI: 10.4230/lipics.socg.2022.18

Peer reviewed articles (11)

On the correlation gap of matroids

Autori: Edin Husić, Zhuan Khye Koh, Georg Loho, László A. Végh
Pubblicato in: Mathematical Programming, Numero 210, 2025, Pagina/e 407-456, ISSN 0025-5610
Editore: Springer Verlag
DOI: 10.1007/s10107-024-02116-w

Simple Iterative Methods for Linear Optimization over Convex Sets

Autori: Dadush, Daniel; Hojny, Christopher; Huiberts, Sophie; Weltge, Stefan
Pubblicato in: Mathematical Programming, 2023, ISSN 1436-4646
Editore: Springer
DOI: 10.1007/s10107-023-02005-8

A simple method for convex optimization in the oracle model

Autori: Daniel Dadush, Christopher Hojny, Sophie Huiberts, Stefan Weltge
Pubblicato in: Mathematical Programming, Numero 206, 2024, Pagina/e 283-304, ISSN 0025-5610
Editore: Springer Verlag
DOI: 10.1007/s10107-023-02005-8

On circuit diameter bounds via circuit imbalances

Autori: Daniel Dadush, Zhuan Khye Koh, Bento Natura, László A. Végh
Pubblicato in: Mathematical Programming, 2024, Pagina/e 631-662, ISSN 0025-5610
Editore: Springer Verlag
DOI: 10.1007/s10107-024-02107-x

From approximate to exact integer programming

Autori: Daniel Dadush, Friedrich Eisenbrand, Thomas Rothvoss
Pubblicato in: Mathematical Programming, Numero 210, 2025, Pagina/e 223-241, ISSN 0025-5610
Editore: Springer Verlag
DOI: 10.1007/s10107-024-02084-1

An Accelerated Newton-Dinkelbach Method and its Application to Two Variables Per Inequality Systems

Autori: Dadush, Daniel; Koh, Zhuan Khye; Natura, Bento; Végh, László A.
Pubblicato in: Mathematics of Operations Research, 2022, ISSN 1526-5471
Editore: INFORMS
DOI: 10.48550/arxiv.2004.08634

On the integrality gap of binary integer programs with Gaussian data

Autori: Sander Borst, Daniel Dadush, Sophie Huiberts, Samarth Tiwari
Pubblicato in: Mathematical Programming, Numero 197, 2023, Pagina/e 1221-1263, ISSN 0025-5610
Editore: Springer Verlag
DOI: 10.1007/s10107-022-01828-1

A nearly optimal randomized algorithm for explorable heap selection

Autori: Sander Borst, Daniel Dadush, Sophie Huiberts, Danish Kashaev
Pubblicato in: Mathematical Programming, Numero 210, 2025, Pagina/e 75-96, ISSN 0025-5610
Editore: Springer Verlag
DOI: 10.1007/s10107-024-02145-5

An Accelerated Newton–Dinkelbach Method and Its Application to Two Variables per Inequality Systems

Autori: Daniel Dadush, Zhuan Khye Koh, Bento Natura, László A. Végh
Pubblicato in: Mathematics of Operations Research, 2022, ISSN 0364-765X
Editore: Institute for Operations Research and the Management Sciences
DOI: 10.1287/moor.2022.1326

Hidden Convexity, Optimization, and Algorithms on Rotation Matrices

Autori: Akshay Ramachandran, Kevin Shu, Alex L. Wang
Pubblicato in: Mathematics of Operations Research, 2024, ISSN 0364-765X
Editore: Institute for Operations Research and the Management Sciences
DOI: 10.1287/moor.2023.0114

A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix

Autori: Dadush, Daniel; Huiberts, Sophie; Natura, Bento, Végh, László A.
Pubblicato in: Mathematical Programming, 2023, ISSN 1436-4646
Editore: Springer
DOI: 10.1007/s10107-023-01956-2