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On Integer Programming and Convolution
TLDR
We show that improving our algorithm for IPs of any fixed number of constraints is equivalent to improving (min, +)-convolution. Expand
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Near-Linear Time Algorithm for n-fold ILPs via Color Coding
TLDR
We study an important case of ILPs $\max\{c^Tx \ \vert\ \mathcal Ax = b, l \leq x \LEq u,\, x \in \mathbb{Z}^{n t} \} with $n\cdot t$ variables and lower and upper bounds $\ell, u\in\mathbb Z^{nt}$. Expand
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On the Configuration-LP of the Restricted Assignment Problem
TLDR
We consider the classical problem of S cheduling on U nrelated M achines . Expand
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A Quasi-Polynomial Approximation for the Restricted Assignment Problem
TLDR
In this paper we study the Restricted Assignment problem, which is the special case where \(p_{ij}\in \{p_j,\infty \}\). Expand
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A note on the integrality gap of the configuration LP for restricted Santa Claus
TLDR
We present a better analysis that shows the integrality gap is not worse than $3 + 5/6 \approx 3.8333$. Expand
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Local search breaks 1.75 for Graph Balancing
TLDR
Graph Balancing was the last one in a group of related problems from literature, for which it was open whether the configuration LP is stronger than previous, simple LP relaxations. Expand
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On Integer Programming, Discrepancy, and Convolution
Integer programs with a constant number of constraints are solvable in pseudo-polynomial time. We give a new algorithm with a better pseudo-polynomial running time than previous results. Moreover, weExpand
  • 9
Block-Structured Integer and Linear Programming in Strongly Polynomial and Near Linear Time
TLDR
We consider integer and linear programming problems for which the linear constraints exhibit a (recursive) block-structure: The problem decomposes into independent and efficiently solvable sub-problems if a small number of constraints is deleted. Expand
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Compact LP Relaxations for Allocation Problems
TLDR
We consider the restricted versions of Scheduling on Unrelated Machines and the Santa Claus problem. Expand
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Online Bin Covering with Limited Migration
TLDR
Semi-online models where decisions may be revoked in a limited way have been studied extensively in the last years. Expand
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