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Dynamically Selecting Composition Algorithms for Economical Composition as a Service

Publications associées (98)

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A ride time-oriented scheduling algorithm for dial-a-ride problems

Nikolaos Geroliminis, Claudia Bongiovanni, Mor Kaspi

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Pergamon-Elsevier Science Ltd2024

In urban air mobility (UAM) networks, takeoff and landing sites, called vertiports, are likely to experience intermittent closures due to, e.g., adverse weather. To ensure safety, all in-flight urban air vehicles (UAVs) in a UAM network must therefore have ...

2024

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Results on Sparse Integer Programming and Geometric Independent Sets

Jana Tabea Cslovjecsek

An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n.Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed p ...

EPFL2023

Toward a remote assessment of walking bout and speed: application in patients with multiple sclerosis

Kamiar Aminian, Farzin Dadashi, Benoît Mariani, Arash Atrsaei

Gait speed as a powerful biomarker of mobility is mostly assessed in controlled environments, e.g. in the clinic. With wearable inertial sensors, gait speed can be estimated in an objective manner. However, most of the previous works have validated the gai ...

2021

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

This article studies a class of nonsmooth decentralized multiagent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a common nonsmooth term. We propose a general primal-dual algorithmic framewor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

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Existing connectivity-oriented performance measures rank road delineation algorithms inconsistently, which makes it difficult to decide which one is best for a given application. We show that these inconsistencies stem from design flaws that make the metri ...

2020

Pipeline Synthesis and Optimization from Branched Feedback Dataflow Programs

Marco Mattavelli, Simone Casale Brunet, Endri Bezati, Anatoly Prihozhy

Large dataflow designs are a result of behavioral specification of modern complex digital systems and/or a result of unfolding and transforming looped and branched programs. Since deep-submicron silicon technology provides large amounts of available resour ...

SPRINGER2020

Learning to Play Sequential Games versus Unknown Opponents

Maryam Kamgarpour, Andreas Krause, Ilija Bogunovic

We consider a repeated sequential game between a learner, who plays first, and an opponent who responds to the chosen action. We seek to design strategies for the learner to successfully interact with the opponent. While most previous approaches consider k ...

Curran Associates, Inc.2020

New Graph Algorithms via Polyhedral Techniques

Jakub Tarnawski

In this thesis we give new algorithms for two fundamental graph problems. We develop novel ways of using linear programming formulations, even exponential-sized ones, to extract structure from problem instances and to guide algorithms in making progress. S ...

EPFL2019