Thin Partitions: Isoperimetric Inequalities and Sampling Algorithms for some Nonconvex Families - Karthekeyan Chandrasekaran; Daniel Dadush; Santosh S. Vempala (CoRR, 2009)

Thin Partitions: Isoperimetric Inequalities and a Sampling Algorithm for Star Shaped Bodies. - Karthekeyan Chandrasekaran; Daniel Dadush; Santosh S. Vempala (SODA, 2010)

Enumerative Algorithms for the Shortest and Closest Lattice Vector Problems in Any Norm via M-Ellipsoid Coverings - Daniel Dadush; Chris Peikert; Santosh S. Vempala (CoRR, 2010)

Enumerative Lattice Algorithms in any Norm Via M-ellipsoid Coverings. - Daniel Dadush; Chris Peikert; Santosh S. Vempala (FOCS, 2011)

Deterministic Construction of an Approximate M-Ellipsoid and its Application to Derandomizing Lattice Algorithms - Daniel Dadush; Santosh S. Vempala (CoRR, 2011)

A O(1/eps^2)^n Time Sieving Algorithm for Approximate Integer Programming - Daniel Dadush (CoRR, 2011)

The Chvátal-Gomory Closure of a Strictly Convex Body. - Daniel Dadush; Santanu S. Dey; Juan Pablo Vielma (Math. Oper. Res., 2011)

The split closure of a strictly convex body. - Daniel Dadush; Santanu S. Dey; Juan Pablo Vielma (Oper. Res. Lett., 2011)

A O(1/ε 2) n -Time Sieving Algorithm for Approximate Integer Programming. - Daniel Dadush (LATIN, 2012)

Deterministic construction of an approximate M-ellipsoid and its applications to derandomizing lattice algorithms. - Daniel Dadush; Santosh S. Vempala (SODA, 2012)

Unconditional differentially private mechanisms for linear queries. - Aditya Bhaskara; Daniel Dadush; Ravishankar Krishnaswamy; Kunal Talwar (STOC, 2012)

Deterministic 2^{O(n)} Algorithms for M-Ellipsoids, Lattice Problems and Volume Estimation - Daniel Dadush; Santosh S. Vempala (CoRR, 2012)

Integer programming, lattice algorithms, and deterministic volume estimation. - Daniel Dadush (2012)

On the Lattice Smoothing Parameter Problem. - Kai-Min Chung; Daniel Dadush; Feng-Hao Liu; Chris Peikert (CCC, 2013)

Algorithms for the Densest Sub-Lattice Problem. - Daniel Dadush; Daniele Micciancio (SODA, 2013)

A Deterministic Polynomial Space Construction for eps-nets under any Norm. - Daniel Dadush (CoRR, 2013)

Near-optimal deterministic algorithms for volume computation via M-ellipsoids. - Daniel Dadush; Santosh S. Vempala (Proc. Natl. Acad. Sci. USA, 2013)

On the Closest Vector Problem with a Distance Guarantee. - Daniel Dadush; Oded Regev 001; Noah Stephens-Davidowitz (CCC, 2014)

A Randomized Sieving Algorithm for Approximate Integer Programming. - Daniel Dadush (Algorithmica, 2014)

Solving the Shortest Vector Problem in $2^n$ Time via Discrete Gaussian Sampling. - Divesh Aggarwal; Daniel Dadush; Oded Regev 001; Noah Stephens-Davidowitz (CoRR, 2014)

On the Chvátal-Gomory closure of a compact convex set. - Daniel Dadush; Santanu S. Dey; Juan Pablo Vielma (Math. Program., 2014)

Faster Deterministic Volume Estimation in the Oracle Model via Thin Lattice Coverings. - Daniel Dadush (SoCG, 2015)

Solving the Closest Vector Problem in 2^n Time - The Discrete Gaussian Strikes Again! - Divesh Aggarwal; Daniel Dadush; Noah Stephens-Davidowitz (FOCS, 2015)

Short Paths on the Voronoi Graph and Closest Vector Problem with Preprocessing. - Daniel Dadush; Nicolas Bonifas (SODA, 2015)

Solving the Shortest Vector Problem in 2n Time Using Discrete Gaussian Sampling: Extended Abstract. - Divesh Aggarwal; Daniel Dadush; Oded Regev 001; Noah Stephens-Davidowitz (STOC, 2015)

On the existence of 0/1 polytopes with high semidefinite extension complexity. - Jop Briët; Daniel Dadush; Sebastian Pokutta (Math. Program., 2015)

On the Lattice Distortion Problem. - Huck Bennett; Daniel Dadush; Noah Stephens-Davidowitz (ESA, 2016)

Towards Strong Reverse Minkowski-Type Inequalities for Lattices. - Daniel Dadush; Oded Regev 001 (FOCS, 2016)

Rescaled Coordinate Descent Methods for Linear Programming. - Daniel Dadush; László A. Végh; Giacomo Zambelli (IPCO, 2016)

Rescaling Algorithms for Linear Programming - Part I: Conic feasibility. - Daniel Dadush; László A. Végh; Giacomo Zambelli (CoRR, 2016)

On the Shadow Simplex Method for Curved Polyhedra. - Daniel Dadush; Nicolai Hähnle (Discret. Comput. Geom., 2016)

Lattice Sparsification and the Approximate Closest Vector Problem. - Daniel Dadush; Gábor Kun (Theory Comput., 2016)

AWGN-Goodness is Enough: Capacity-Achieving Lattice Codes based on Dithered Probabilistic Shaping. - Antonio Campello; Daniel Dadush (CoRR, 2017)

Balancing Vectors in Any Norm. - Daniel Dadush; Aleksandar Nikolov; Kunal Talwar; Nicole Tomczak-Jaegermann (FOCS, 2018)

Lattice-based Locality Sensitive Hashing is Optimal. - Karthekeyan Chandrasekaran; Daniel Dadush; Venkata Gandikota; Elena Grigorescu (ITCS, 2018)

Fast, Deterministic and Sparse Dimensionality Reduction. - Daniel Dadush; Cristóbal Guzmán; Neil Olver (SODA, 2018)

On approximating the covering radius and finding dense lattice subspaces. - Daniel Dadush (STOC, 2019)

An Algorithm for Komlós Conjecture Matching Banaszczyk's Bound. - Nikhil Bansal 001; Daniel Dadush; Shashwat Garg (SIAM J. Comput., 2019)

AWGN-Goodness Is Enough: Capacity-Achieving Lattice Codes Based on Dithered Probabilistic Shaping. - Antonio Campello; Daniel Dadush; Cong Ling 001 (IEEE Trans. Inf. Theory, 2019)

The Gram-Schmidt Walk: A Cure for the Banaszczyk Blues. - Nikhil Bansal 001; Daniel Dadush; Shashwat Garg; Shachar Lovett (Theory Comput., 2019)

Towards a Constructive Version of Banaszczyk's Vector Balancing Theorem. - Daniel Dadush; Shashwat Garg; Shachar Lovett; Aleksandar Nikolov (Theory Comput., 2019)

Smoothed Analysis of the Simplex Method. - Daniel Dadush; Sophie Huiberts (Beyond the Worst-Case Analysis of Algorithms, 2020)

On the Complexity of Branching Proofs. - Daniel Dadush; Samarth Tiwari (CCC, 2020)

Revisiting Tardos's Framework for Linear Programming: Faster Exact Solutions using Approximate Solvers. - Daniel Dadush; Bento Natura; László A. Végh (FOCS, 2020)

Simple Iterative Methods for Linear Optimization over Convex Sets. - Daniel Dadush; Christopher Hojny; Sophie Huiberts; Stefan Weltge (CoRR, 2020)

Rescaling Algorithms for Linear Conic Feasibility. - Daniel Dadush; László A. Végh; Giacomo Zambelli (Math. Oper. Res., 2020)

A Friendly Smoothed Analysis of the Simplex Method. - Daniel Dadush; Sophie Huiberts (SIAM J. Comput., 2020)

Majorizing Measures for the Optimizer. - Sander Borst; Daniel Dadush; Neil Olver; Makrand Sinha (ITCS, 2021)

Geometric Rescaling Algorithms for Submodular Function Minimization. - Dan Dadush; László A. Végh; Giacomo Zambelli (Math. Oper. Res., 2021)

Asymptotic Bounds on the Combinatorial Diameter of Random Polytopes. - Gilles Bonnet; Daniel Dadush; Uri Grupel; Sophie Huiberts; Galyna Livshyts (SoCG, 2022)

Interior point methods are not worse than Simplex. - Xavier Allamigeon; Daniel Dadush; Georg Loho; Bento Natura; László A. Végh (FOCS, 2022)

On finding exact solutions of linear programs in the oracle model. - Daniel Dadush; László A. Végh; Giacomo Zambelli (SODA, 2022)

A new framework for matrix discrepancy: partial coloring bounds via mirror descent. - Daniel Dadush; Haotian Jiang; Victor Reis (STOC, 2022)

Optimizing Low Dimensional Functions over the Integers. - Daniel Dadush; Arthur Léonard; Lars Rohwedder; José Verschae (IPCO, 2023)

Integrality Gaps for Random Integer Programs via Discrepancy. - Sander Borst; Daniel Dadush; Dan Mikulincer (SODA, 2023)

An Accelerated Newton-Dinkelbach Method and Its Application to Two Variables per Inequality Systems. - Daniel Dadush; Zhuan Khye Koh; Bento Natura; László A. Végh (Math. Oper. Res., 2023)

On the integrality gap of binary integer programs with Gaussian data. - Sander Borst; Daniel Dadush; Sophie Huiberts; Samarth Tiwari (Math. Program., 2023)

Strongly Polynomial Frame Scaling to High Precision. - Daniel Dadush; Akshay Ramachandran (SODA, 2024)

A Strongly Polynomial Algorithm for Linear Programs with At Most Two Nonzero Entries per Row or Column. - Daniel Dadush; Zhuan Khye Koh; Bento Natura; Neil Olver; László A. Végh (STOC, 2024)

A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. - Daniel Dadush; Sophie Huiberts; Bento Natura; László A. Végh (Math. Program., 2024)

A simple method for convex optimization in the oracle model. - Daniel Dadush; Christopher Hojny; Sophie Huiberts; Stefan Weltge (Math. Program., 2024)

On circuit diameter bounds via circuit imbalances. - Daniel Dadush; Zhuan Khye Koh; Bento Natura; László A. Végh (Math. Program., 2024)

Introduction: ACM-SIAM Symposium on Discrete Algorithms (SODA) 2022 Special Issue. - Daniel Dadush; Martin Milanic; Tami Tamir (ACM Trans. Algorithms, 2024)

A Strongly Polynomial Algorithm for Linear Programs with at Most Two Non-Zero Entries per Row or Column (Invited Talk). - Daniel Dadush; Zhuan Khye Koh; Bento Natura; Neil Olver; László A. Végh (STACS, 2025)

A nearly optimal randomized algorithm for explorable heap selection. - Sander Borst; Daniel Dadush; Sophie Huiberts; Danish Kashaev (Math. Program., 2025)

From approximate to exact integer programming. - Daniel Dadush; Friedrich Eisenbrand; Thomas Rothvoss (Math. Program., 2025)