Solving Routing Problems Using Quantum and Hybrid Algorithms
Explore quantum and hybrid algorithms for solving NP-hard routing problems, comparing them with classical solvers and discussing future research directions.
Personalized Shift Scheduling Problems: From Modelling to Efficient Resolution
Explore personalized shift scheduling challenges, modeling techniques, and efficient resolution methods for complex employee scheduling problems like nurse rostering.
Álgebras de Configuración de Brauer y sus Aplicaciones en Criptografía y Ciencias
Explora las álgebras de configuración de Brauer, su origen y aplicaciones en criptografía, ecuaciones de Yang-Baxter, teoría de grafos y optimización combinatoria.
Algorithms for Rank-1 Bimatrix Games
Explore algorithms for solving rank-1 bimatrix games efficiently, including polynomial-time methods for finding Nash equilibria and path-following techniques. Discusses complexity, uniqueness, and parameterized approaches.
Beyond Value Iteration for Parity Games - Strategy Iteration with Universal Trees
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.
Chance Constrained Simultaneous Task Allocation and Path Planning for Multi-Robot Systems
Explore multi-robot task allocation and path planning with probabilistic performance guarantees. Learn algorithmic approaches for optimizing team performance in open environments.
Spectral Aspects of Symmetric Matrix Signings
Explore symmetric matrix signings, their spectral aspects, and applications in graph theory, polynomial identity testing, and algorithmic problems.
Constructing Extended Formulations
Explore advanced techniques for constructing extended formulations in combinatorial optimization, focusing on polytopes, matchings, cycles, and spanning trees in various graph types.
Theory Seminar - Submodular Maximization
Explore submodular maximization techniques, recent advances, and open questions in combinatorial optimization with Professor Niv Buchbinder's comprehensive theory seminar.
Faster Energy Maximization for Faster Maximum Flow
Explore advanced techniques for solving maximum flow problems in undirected graphs, focusing on energy maximization and weight reduction strategies to improve algorithmic efficiency.
Deep Learning for Combinatorial Optimization - Count Your Flops & Make Your Flops Count
Explores deep learning for combinatorial optimization, focusing on reducing computation through learned models while balancing solution quality. Discusses practical examples, challenges, and future research directions.
How Much Data Is Sufficient to Learn High-Performing Algorithms?
Explore data-driven algorithm design's impact on performance, focusing on generalization guarantees for combinatorial algorithms with piecewise-structured parameter functions.
A Framework for Differentiable Discovery of Graph Algorithms
Explore graph algorithm discovery using deep learning and tree decomposition. Learn effective techniques for NP-complete problems with interpretable results and expanded search space.
Neural Network Verification as Piecewise Linear Optimization
Neural network verification as piecewise linear optimization: exploring robust methods to prove model reliability against attacks, using LP and MIP formulations for efficient problem-solving in various network types.
Neil Olver: On the Integrality Gap of the Prize Collecting Steiner Forest LP
Explores the integrality gap of the prize collecting Steiner forest LP, disproving the belief it was 2 and showing it's at least 9/4, with implications for approximation algorithms in combinatorial optimization.
Gomory Mixed Integer Cuts Are Optimal
Explores the theoretical superiority of Gomory mixed-integer cuts in integer programming, demonstrating their optimality in maximizing volume cut-off from the nonnegative orthant in infinite group relaxations.
Viswanath Nagarajan - Stochastic Load Balancing on Unrelated Machines
Explores stochastic load balancing on unrelated machines, presenting a constant factor approximation algorithm for minimizing expected makespan. Discusses LP relaxation and rounding techniques.
Finding Perfect Matchings in Bipartite Hypergraphs
Explore efficient algorithms for finding perfect matchings in bipartite hypergraphs, extending Haxell's condition and the Hungarian algorithm to hypergraph structures.
Louis Theran: Rigidity of Random Graphs in Higher Dimensions
Explore rigidity properties of random graphs in higher dimensions and their connection to matrix completion, with insights on thresholds and optimal conditions.
Recent Results on Maximizing Submodular Functions
Explore recent advancements in submodular maximization, covering constrained and unconstrained scenarios for monotone and non-monotone functions within combinatorial optimization.
Provable Submodular Function Minimization via Fujishige Wolfe Algorithm
Explore submodular function minimization through the Fujishige-Wolfe algorithm, analyzing its convergence and implications for combinatorial optimization.