Concept

Greedy coloring

Related publications (65)

Multi-robot task allocation for safe planning against stochastic hazard dynamics

We address multi-robot safe mission planning in uncertain dynamic environments. This problem arises in several applications including safety-critical exploration, surveillance, and emergency rescue missions. Computation of a multi-robot optimal control pol ...

2023

Approximation Algorithms for Allocation and Network Design

Etienne Michel François Bamas

In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

EPFL2023

Performance guarantees of forward and reverse greedy algorithms for minimizing nonsupermodular nonsubmodular functions on a matroid

Maryam Kamgarpour, Orcun Karaca

This letter studies the problem of minimizing increasing set functions, equivalently, maximizing decreasing set functions, over the base matroid. This setting has received great interest, since it generalizes several applied problems including actuator and ...

2021

Frequency-Domain Non-intrusive Greedy Model Order Reduction Based on Minimal Rational Approximation

Fabio Nobile, Davide Pradovera

We present a technique for Model Order Reduction (MOR) of frequency-domain problems relying on rational interpolation of vector-valued functions. The selection of the sample points is carried out adaptively according to a greedy procedure. We describe seve ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

Cluster-and-Conquer: When Randomness Meets Graph Locality

Anne-Marie Kermarrec, Olivier Ruas

K-Nearest-Neighbors (KNN) graphs are central to many emblematic data mining and machine-learning applications. Some of the most efficient KNN graph algorithms are incremental and local: they start from a random graph, which they incrementally improve by tr ...

IEEE COMPUTER SOC2021

Multi-robot task allocation for safe planning against stochastic hazard dynamics

Maryam Kamgarpour, Orcun Karaca

This paper considers the problem of multi-robot safe mission planning in uncertain dynamic environments. This problem arises in several applications including safety-critical exploration, surveillance, and emergency rescue missions. Computation of a multi- ...

2021

How to Match in Modern Computational Settings

Buddhima Ruwanmini Gamlath Gamlath Ralalage

This thesis focuses on the maximum matching problem in modern computational settings where the algorithms have to make decisions with partial information.First, we consider two stochastic models called query-commit and price-of-information where the algori ...

EPFL2021

Actuator Placement under Structural Controllability using Forward and Reverse Greedy Algorithms

Maryam Kamgarpour, Tyler Summers, Baiwei Guo, Orcun Karaca

Actuator placement is an active field of research which has received significant attention for its applications in complex dynamical networks. In this paper, we study the problem of finding a set of actuator placements minimizing the metric that measures t ...

2020

MATHICSE Technical Report : Frequency-domain non-intrusive greedy Model Order Reduction based on minimal rational approximation

Fabio Nobile, Davide Pradovera

MATHICSE2020

A Reinforcement Learning Approach to Train Routing and Scheduling

Zora Oswald

Good train scheduling for a big network with many trains is very hard to achieve. As the trains are competing for the tracks with one another, the number of constraints grows rapidly. Trying to take advantage of emerging technologies in the areas of optimi ...

2020

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