52 citations · 131 across the 29 of their papers we have counts for
18 papers · 1 filter
Optimizing Low Dimensional Functions over the Integers
Daniel Dadush, Arthur Léonard, Lars Rohwedder +1
We consider box-constrained integer programs with objective , where is a "complicated" function with an dimensional domain. Here we assume we have …
A nearly optimal randomized algorithm for explorable heap selection
Sander Borst, Daniel Dadush, Sophie Huiberts +1
Explorable heap selection is the problem of selecting the th smallest value in a binary heap. The key values can only be accessed by traversing through the underlying infinite b…
A New Framework for Matrix Discrepancy: Partial Coloring Bounds via Mirror Descent
Daniel Dadush, Haotian Jiang, Victor Reis
Motivated by the Matrix Spencer conjecture, we study the problem of finding signed sums of matrices with a small matrix norm. A well-known strategy to obtain these signs is to prov…
An Accelerated Newton-Dinkelbach Method and its Application to Two Variables Per Inequality Systems
Daniel Dadush, Zhuan Khye Koh, Bento Natura +1
We present an accelerated, or 'look-ahead' version of the Newton-Dinkelbach method, a well-known technique for solving fractional and parametric optimization problems. This acceler…
Lattice-based Locality Sensitive Hashing is Optimal
Karthekeyan Chandrasekaran, Daniel Dadush, Venkata Gandikota +1
Locality sensitive hashing (LSH) was introduced by Indyk and Motwani (STOC `98) to give the first sublinear time algorithm for the c-approximate nearest neighbor (ANN) problem usin…
A Friendly Smoothed Analysis of the Simplex Method
Daniel Dadush, Sophie Huiberts
Explaining the excellent practical performance of the simplex method for linear programming has been a major topic of research for over 50 years. One of the most successful framewo…