Delta-modular ILP Problems of Bounded Codimension, Discrepancy, and Convolution (new version)
M. Cherniavskii, D. Gribanov, D. Malyshev, P. M. Pardalos

TL;DR
This paper introduces improved algorithms for bounded codimension ILP problems, providing tighter complexity bounds and exploring special cases with applications in computational complexity and algebraic transforms.
Contribution
It presents new algorithms with enhanced complexity bounds for ILP problems parameterized by codimension and discrepancy, and analyzes the tropical convolution and generalized DFT over Abelian groups.
Findings
Optimized algorithms with subexponential complexity in terms of elta
Special case algorithms for k=0,1 with improved bounds
Error analysis of generalized DFT in Word-RAM model
Abstract
For integers and a cost vector , we study two fundamental integer linear programming (ILP) problems: \[ \text{(Standard Form)} \quad \max\bigl\{c^\top x \colon Ax = b,\ x \in Z^n_{\geq 0}\bigr\} \text{ with } A \in Z^{k \times n}, \text{rank}(A) = k, b \in Z^k, \] \[ \text{(Canonical Form)} \quad \max\bigl\{c^\top x \colon Ax \leq b,\ x \in Z^n\bigr\} \text{ with } A \in Z^{(n+k) \times n}, \text{rank}(A) = n, b \in Z^{n+k}. \] We present improved algorithms for both problems and their feasibility versions, parameterized by and , where denotes the maximum absolute value of subdeterminants of . Our main complexity results, stated in terms of required arithmetic operations, are: \[ \text{Optimization:}\quad O(\log k)^{2k} \cdot \Delta^2 / 2^{\Omega(\sqrt{\log \Delta})} + 2^{O(k)} \cdot…
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Taxonomy
TopicsAdvanced Numerical Analysis Techniques · Digital Filter Design and Implementation · Electromagnetic Scattering and Analysis
