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Explores graph partitioning with lp-norm multiway cut, unifying min-sum and min-max variants. Discusses hardness, integrality gap, and approximation algorithm for this generalized problem.
Explore SIM-bodies as generalized permutahedra, their role in Straight-Jacket Auctions, and the application of computer algebra for determining optimal prices and revenues in auction theory.
Explore polyhedra diameter and its impact on simplex method complexity. Overview previous findings, recent results, and open questions in this mathematical field.
Explore new combinatorial condition numbers for linear and integer programs, their relation to existing measures, and their impact on circuit diameter bounds and simplex methods.
Explores strategy iteration framework for parity games using universal trees, aiming to overcome quasi-polynomial barriers and improve upon value iteration algorithms for efficient game solving.
Binary scalar products: Proving a conjecture on 2-level polytopes, exploring their unique properties and demonstrating that the product of vertices and facets is bounded by d2^(d+1) for d-dimensional polytopes.
Explore tropical linear regression, its connection to mean payoff games, and applications in auction theory. Learn about equilibrium prices and quantifying market distances.
Explores separation theorems in signed tropical convexities, comparing TO and TC-convexities. Presents new results on hyperplane separation, characterizes segments and hemi-spaces, and proves equivalence for generic point collections.
Explore the geometric perspective on pivot rules in linear programming, connecting polyhedra, simplex methods, and arborescences to gain insights into optimization algorithms.
Explores steepest descent in 0/1 LPs, proving polynomial-length paths and developing a new pivot rule for the Simplex method. Unifies circuit and edge steps, advancing understanding of combinatorial optimization.
Explore parameterized complexity and its applications in discrete optimization, focusing on LP-guided techniques, Lenstra's algorithm, and structured ILPs using Graver bases.
Explore advanced approximation algorithms for network design, focusing on connectivity augmentation problems and recent developments in combinatorial optimization techniques.
Explore parameterized complexity, focusing on LP-related methods. Learn branching, color coding, kernelization, and dynamic programming techniques for algorithm design and optimization.
Explore advanced network design techniques for increasing graph connectivity, focusing on augmentation problems and recent developments in combinatorial optimization.
Explore interior point methods for optimization, their recent advancements, and applications in solving various continuous and combinatorial problems efficiently.
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