Daniel Dadush

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 67

Top Venues

Publications

Daniel Dadush, Sophie Huiberts, Bento Natura, László A. Végh
A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. Math. Program. 204 (1) (2024)
Daniel Dadush, Martin Milanic, Tami Tamir
Introduction: ACM-SIAM Symposium on Discrete Algorithms (SODA) 2022 Special Issue. ACM Trans. Algorithms 20 (3) (2024)
Daniel Dadush, Christopher Hojny, Sophie Huiberts, Stefan Weltge
A simple method for convex optimization in the oracle model. Math. Program. 206 (1) (2024)
Daniel Dadush, Zhuan Khye Koh, Bento Natura, Neil Olver, László A. Végh
A Strongly Polynomial Algorithm for Linear Programs with At Most Two Nonzero Entries per Row or Column. STOC (2024)
Daniel Dadush, Akshay Ramachandran
Strongly Polynomial Frame Scaling to High Precision. SODA (2024)
Daniel Dadush, Akshay Ramachandran
Strongly Polynomial Frame Scaling to High Precision. CoRR (2024)
Daniel Dadush, Zhuan Khye Koh, Bento Natura, László A. Végh
On circuit diameter bounds via circuit imbalances. Math. Program. 206 (1) (2024)
Daniel Dadush, Friedrich Eisenbrand, Thomas Rothvoss
From Approximate to Exact Integer Programming. IPCO (2023)
Sander Borst, Daniel Dadush, Sophie Huiberts, Samarth Tiwari
On the integrality gap of binary integer programs with Gaussian data. Math. Program. 197 (2) (2023)
Sander Borst, Daniel Dadush, Sophie Huiberts, Danish Kashaev
A Nearly Optimal Randomized Algorithm for Explorable Heap Selection. IPCO (2023)
Daniel Dadush, Arthur Léonard, Lars Rohwedder, José Verschae
Optimizing Low Dimensional Functions over the Integers. CoRR (2023)
Sander Borst, Daniel Dadush, Dan Mikulincer
Integrality Gaps for Random Integer Programs via Discrepancy. SODA (2023)
Daniel Dadush, Arthur Léonard, Lars Rohwedder, José Verschae
Optimizing Low Dimensional Functions over the Integers. IPCO (2023)
Xavier Allamigeon, Daniel Dadush, Georg Loho, Bento Natura, László A. Végh
Interior point methods are not worse than Simplex. CoRR (2022)
Sander Borst, Daniel Dadush, Sophie Huiberts, Danish Kashaev
A nearly optimal randomized algorithm for explorable heap selection. CoRR (2022)
Daniel Dadush, Haotian Jiang, Victor Reis
A new framework for matrix discrepancy: partial coloring bounds via mirror descent. STOC (2022)
Gilles Bonnet, Daniel Dadush, Uri Grupel, Sophie Huiberts, Galyna Livshyts
Asymptotic Bounds on the Combinatorial Diameter of Random Polytopes. SoCG (2022)
Daniel Dadush, Christopher Hojny, Sophie Huiberts, Stefan Weltge
A Simple Method for Convex Optimization in the Oracle Model. IPCO (2022)
Daniel Dadush, Friedrich Eisenbrand, Thomas Rothvoss
From approximate to exact integer programming. CoRR (2022)
Daniel Dadush, László A. Végh, Giacomo Zambelli
On finding exact solutions of linear programs in the oracle model. SODA (2022)
Daniel Dadush, Zhuan Khye Koh, Bento Natura, László A. Végh
On Circuit Diameter Bounds via Circuit Imbalances. IPCO (2022)
Xavier Allamigeon, Daniel Dadush, Georg Loho, Bento Natura, László A. Végh
Interior point methods are not worse than Simplex. FOCS (2022)
Sander Borst, Daniel Dadush, Neil Olver, Makrand Sinha
Majorizing Measures for the Optimizer. ITCS (2021)
Sander Borst, Daniel Dadush, Sophie Huiberts, Samarth Tiwari
On the Integrality Gap of Binary Integer Programs with Gaussian Data. IPCO (2021)
Daniel Dadush, Haotian Jiang, Victor Reis
A New Framework for Matrix Discrepancy: Partial Coloring Bounds via Mirror Descent. CoRR (2021)
Daniel Dadush, Zhuan Khye Koh, Bento Natura, László A. Végh
An Accelerated Newton-Dinkelbach Method and Its Application to Two Variables per Inequality Systems. ESA (2021)
Gilles Bonnet, Daniel Dadush, Uri Grupel, Sophie Huiberts, Galyna Livshyts
Asymptotic Bounds on the Combinatorial Diameter of Random Polytopes. CoRR (2021)
Daniel Dadush, Zhuan Khye Koh, Bento Natura, László A. Végh
On Circuit Diameter Bounds via Circuit Imbalances. CoRR (2021)
Daniel Dadush, Samarth Tiwari
On the Complexity of Branching Proofs. Computational Complexity Conference (2020)
Daniel Dadush, Samarth Tiwari
On the Complexity of Branching Proofs. CoRR (2020)
Daniel Dadush, Sophie Huiberts, Bento Natura, László A. Végh
A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. STOC (2020)
Sander Borst, Daniel Dadush, Sophie Huiberts, Samarth Tiwari
On the Integrality Gap of Binary Integer Programs with Gaussian Data. CoRR (2020)
Daniel Dadush, Christopher Hojny, Sophie Huiberts, Stefan Weltge
Simple Iterative Methods for Linear Optimization over Convex Sets. CoRR (2020)
Daniel Dadush, Sophie Huiberts
A Friendly Smoothed Analysis of the Simplex Method. SIAM J. Comput. 49 (5) (2020)
Sander Borst, Daniel Dadush, Neil Olver, Makrand Sinha
Majorizing Measures for the Optimizer. CoRR (2020)
Daniel Dadush, László A. Végh, Giacomo Zambelli
Rescaling Algorithms for Linear Conic Feasibility. Math. Oper. Res. 45 (2) (2020)
Daniel Dadush, Bento Natura, László A. Végh
Revisiting Tardos's Framework for Linear Programming: Faster Exact Solutions using Approximate Solvers. FOCS (2020)
Daniel Dadush, Bento Natura, László A. Végh
Revisiting Tardos's Framework for Linear Programming: Faster Exact Solutions using Approximate Solvers. CoRR (2020)
Nikhil Bansal, Daniel Dadush, Shashwat Garg, Shachar Lovett
The Gram-Schmidt Walk: A Cure for the Banaszczyk Blues. Theory Comput. 15 (2019)
Daniel Dadush
On approximating the covering radius and finding dense lattice subspaces. STOC (2019)
Antonio Campello, Daniel Dadush, Cong Ling
AWGN-Goodness Is Enough: Capacity-Achieving Lattice Codes Based on Dithered Probabilistic Shaping. IEEE Trans. Inf. Theory 65 (3) (2019)
Daniel Dadush, Sophie Huiberts, Bento Natura, László A. Végh
A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. CoRR (2019)
Daniel Dadush, Shashwat Garg, Shachar Lovett, Aleksandar Nikolov
Towards a Constructive Version of Banaszczyk's Vector Balancing Theorem. Theory Comput. 15 (2019)
Nikhil Bansal, Daniel Dadush, Shashwat Garg
An Algorithm for Komlós Conjecture Matching Banaszczyk's Bound. SIAM J. Comput. 48 (2) (2019)
Karthekeyan Chandrasekaran, Daniel Dadush, Venkata Gandikota, Elena Grigorescu
Lattice-based Locality Sensitive Hashing is Optimal. ITCS (2018)
Daniel Dadush, Cristóbal Guzmán, Neil Olver
Fast, Deterministic and Sparse Dimensionality Reduction. SODA (2018)
Daniel Dadush, László A. Végh, Giacomo Zambelli
Geometric Rescaling Algorithms for Submodular Function Minimization. SODA (2018)
Nikhil Bansal, Daniel Dadush, Shashwat Garg, Shachar Lovett
The gram-schmidt walk: a cure for the Banaszczyk blues. STOC (2018)
Daniel Dadush, Aleksandar Nikolov, Kunal Talwar, Nicole Tomczak-Jaegermann
Balancing Vectors in Any Norm. FOCS (2018)
Daniel Dadush, Sophie Huiberts
A friendly smoothed analysis of the simplex method. STOC (2018)
Daniel Dadush, László A. Végh, Giacomo Zambelli
Geometric Rescaling Algorithms for Submodular Function Minimization. CoRR (2017)
Daniel Dadush, Sophie Huiberts
A Friendly Smoothed Analysis of the Simplex Method. CoRR (2017)
Nikhil Bansal, Daniel Dadush, Shashwat Garg, Shachar Lovett
The Gram-Schmidt Walk: A Cure for the Banaszczyk Blues. CoRR (2017)
Karthekeyan Chandrasekaran, Daniel Dadush, Venkata Gandikota, Elena Grigorescu
Lattice-based Locality Sensitive Hashing is Optimal. CoRR (2017)
Antonio Campello, Daniel Dadush
AWGN-Goodness is Enough: Capacity-Achieving Lattice Codes based on Dithered Probabilistic Shaping. CoRR (2017)
Daniel Dadush, Shashwat Garg, Shachar Lovett, Aleksandar Nikolov
Towards a Constructive Version of Banaszczyk's Vector Balancing Theorem. CoRR (2016)
Daniel Dadush, László A. Végh, Giacomo Zambelli
Rescaling Algorithms for Linear Programming - Part I: Conic feasibility. CoRR (2016)
Daniel Dadush, Shashwat Garg, Shachar Lovett, Aleksandar Nikolov
Towards a Constructive Version of Banaszczyk's Vector Balancing Theorem. APPROX-RANDOM (2016)
Huck Bennett, Daniel Dadush, Noah Stephens-Davidowitz
On the Lattice Distortion Problem. ESA (2016)
Daniel Dadush, Oded Regev
Towards Strong Reverse Minkowski-Type Inequalities for Lattices. FOCS (2016)
Daniel Dadush, László A. Végh, Giacomo Zambelli
Rescaled Coordinate Descent Methods for Linear Programming. IPCO (2016)
Huck Bennett, Daniel Dadush, Noah Stephens-Davidowitz
On the Lattice Distortion Problem. CoRR (2016)
Daniel Dadush, Oded Regev
Towards Strong Reverse Minkowski-type Inequalities for Lattices. CoRR (2016)
Daniel Dadush, Nicolai Hähnle
On the Shadow Simplex Method for Curved Polyhedra. Discret. Comput. Geom. 56 (4) (2016)
Nikhil Bansal, Daniel Dadush, Shashwat Garg
An Algorithm for Komlós Conjecture Matching Banaszczyk's Bound. FOCS (2016)
Daniel Dadush, Gábor Kun
Lattice Sparsification and the Approximate Closest Vector Problem. Theory Comput. 12 (1) (2016)
Nikhil Bansal, Daniel Dadush, Shashwat Garg
An Algorithm for Komlós Conjecture Matching Banaszczyk's bound. CoRR (2016)
Divesh Aggarwal, Daniel Dadush, Noah Stephens-Davidowitz
Solving the Closest Vector Problem in $2^n$ Time - The Discrete Gaussian Strikes Again! CoRR (2015)
Divesh Aggarwal, Daniel Dadush, Noah Stephens-Davidowitz
Solving the Closest Vector Problem in 2^n Time - The Discrete Gaussian Strikes Again! FOCS (2015)
Daniel Dadush, Nicolai Hähnle
On the Shadow Simplex Method for Curved Polyhedra. SoCG (2015)
Jop Briët, Daniel Dadush, Sebastian Pokutta
On the existence of 0/1 polytopes with high semidefinite extension complexity. Math. Program. 153 (1) (2015)
Daniel Dadush, Nicolas Bonifas
Short Paths on the Voronoi Graph and Closest Vector Problem with Preprocessing. SODA (2015)
Divesh Aggarwal, Daniel Dadush, Oded Regev, Noah Stephens-Davidowitz
Time Using Discrete Gaussian Sampling: Extended Abstract. STOC (2015)
Daniel Dadush
Faster Deterministic Volume Estimation in the Oracle Model via Thin Lattice Coverings. SoCG (2015)
Kai-Min Chung, Daniel Dadush, Feng-Hao Liu, Chris Peikert
On the Lattice Smoothing Parameter Problem. CoRR (2014)
Divesh Aggarwal, Daniel Dadush, Oded Regev, Noah Stephens-Davidowitz
Solving the Shortest Vector Problem in $2^n$ Time via Discrete Gaussian Sampling. CoRR (2014)
Daniel Dadush, Oded Regev, Noah Stephens-Davidowitz
On the Closest Vector Problem with a Distance Guarantee. CoRR (2014)
Nicolas Bonifas, Daniel Dadush
Short Paths on the Voronoi Graph and the Closest Vector Problem with Preprocessing. CoRR (2014)
Daniel Dadush
A Randomized Sieving Algorithm for Approximate Integer Programming. Algorithmica 70 (2) (2014)
Daniel Dadush, Nicolai Hähnle
On the Shadow Simplex Method for Curved Polyhedra. CoRR (2014)
Daniel Dadush, Oded Regev, Noah Stephens-Davidowitz
On the Closest Vector Problem with a Distance Guarantee. Computational Complexity Conference (2014)
Daniel Dadush, Santanu S. Dey, Juan Pablo Vielma
On the Chvátal-Gomory closure of a compact convex set. Math. Program. 145 (1-2) (2014)
Daniel Dadush, Gábor Kun
Lattice Sparsification and the Approximate Closest Vector Problem. SODA (2013)
Jop Briët, Daniel Dadush, Sebastian Pokutta
On the existence of 0/1 polytopes with high semidefinite extension complexity CoRR (2013)
Daniel Dadush
A Deterministic Polynomial Space Construction for eps-nets under any Norm. CoRR (2013)
Kai-Min Chung, Daniel Dadush, Feng-Hao Liu, Chris Peikert
On the Lattice Smoothing Parameter Problem. Computational Complexity Conference (2013)
Daniel Dadush, Daniele Micciancio
Algorithms for the Densest Sub-Lattice Problem. SODA (2013)
Jop Briët, Daniel Dadush, Sebastian Pokutta
On the Existence of 0/1 Polytopes with High Semidefinite Extension Complexity. ESA (2013)
Daniel Dadush, Santosh S. Vempala
Near-optimal deterministic algorithms for volume computation via M-ellipsoids. Proc. Natl. Acad. Sci. USA 110 (48) (2013)
Daniel Dadush, Gábor Kun
Lattice Sparsification and the Approximate Closest Vector Problem CoRR (2012)
Daniel Dadush, Santosh S. Vempala
Deterministic 2^{O(n)} Algorithms for M-Ellipsoids, Lattice Problems and Volume Estimation CoRR (2012)
Daniel Dadush, Santosh S. Vempala
Deterministic construction of an approximate M-ellipsoid and its applications to derandomizing lattice algorithms. SODA (2012)
Daniel Dadush
A O(1/ε 2) n -Time Sieving Algorithm for Approximate Integer Programming. LATIN (2012)
Aditya Bhaskara, Daniel Dadush, Ravishankar Krishnaswamy, Kunal Talwar
Unconditional differentially private mechanisms for linear queries. STOC (2012)
Daniel Dadush, Santanu S. Dey, Juan Pablo Vielma
The Chvátal-Gomory Closure of a Strictly Convex Body. Math. Oper. Res. 36 (2) (2011)
Daniel Dadush, Santanu S. Dey, Juan Pablo Vielma
On the Chvátal-Gomory Closure of a Compact Convex Set. IPCO (2011)
Daniel Dadush
A O(1/eps^2)^n Time Sieving Algorithm for Approximate Integer Programming CoRR (2011)
Daniel Dadush, Santanu S. Dey, Juan Pablo Vielma
The split closure of a strictly convex body. Oper. Res. Lett. 39 (2) (2011)
Daniel Dadush, Santosh S. Vempala
Deterministic Construction of an Approximate M-Ellipsoid and its Application to Derandomizing Lattice Algorithms CoRR (2011)
Daniel Dadush, Chris Peikert, Santosh S. Vempala
Enumerative Lattice Algorithms in any Norm Via M-ellipsoid Coverings. FOCS (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Daniel Dadush