20 research outputs found

    Lexicographically Fair Learning: Algorithms and Generalization

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    We extend the notion of minimax fairness in supervised learning problems to its natural conclusion: lexicographic minimax fairness (or lexifairness for short). Informally, given a collection of demographic groups of interest, minimax fairness asks that the error of the group with the highest error be minimized. Lexifairness goes further and asks that amongst all minimax fair solutions, the error of the group with the second highest error should be minimized, and amongst all of those solutions, the error of the group with the third highest error should be minimized, and so on. Despite its naturalness, correctly defining lexifairness is considerably more subtle than minimax fairness, because of inherent sensitivity to approximation error. We give a notion of approximate lexifairness that avoids this issue, and then derive oracle-efficient algorithms for finding approximately lexifair solutions in a very general setting. When the underlying empirical risk minimization problem absent fairness constraints is convex (as it is, for example, with linear and logistic regression), our algorithms are provably efficient even in the worst case. Finally, we show generalization bounds - approximate lexifairness on the training sample implies approximate lexifairness on the true distribution with high probability. Our ability to prove generalization bounds depends on our choosing definitions that avoid the instability of naive definitions

    Coalitional model predictive control for systems of systems

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    An aspect so far rarely contemplated in distributed control problems is the explicit consideration of individual (local) interests of the components of a complex system. Indeed, the focus of the majority of the literature about distributed control has been the overall system performance. While on one hand this permitted to address fundamental properties of centralized control, such as system-wide optimality and stability, one the other hand it implied assuming unrestricted cooperation across local controllers. However, when dealing with multi-agent systems with a strong heterogeneous character, cooperation between the agents cannot be taken for granted (due to, for example, logistics, market competition), and selfish interests may not be neglected. Another critical point that must be kept into consideration is the diversity characterizing systems of systems (SoS), yielding very complex interactions between the agents involved (one example of such system is the smart grid). In order to tackle such inherent aspects of SoS, the research presented in this thesis has been concerned with the development of a novel framework, the coalitional control, that extends the scope of advanced control methods (in particular MPC) by drawing concepts from cooperative game theory that are suited for the inherent heterogeneity of SoS, providing as well an economical interpretation useful to explicitly take into account local selfish interests. Thus, coalitional control aims at governing the association/dissociation dynamics of the agents controlling the system, according to the expected benefits of their possible cooperation. From a control theoretical perspective, this framework is founded on the theory of switched systems and variable structure/topology networked systems, topics that are recently experiencing a renewed interest within the community. The main concepts and challenges in coalitional control, and the links with cooperative network game theory are presented in this document, tracing a path from model partitioning to the control schemes whose principles delineate the idea of coalitional control. This thesis focuses on two basic architectures: (i) a hierarchically supervised evolution of the coalitional structure, and (ii) a protocol for autonomous negotiation between the agents, with specific mechanisms for benefit redistribution, leading to the emergence of cooperating clusters.Premio Extraordinario de Doctorado U

    LIPIcs, Volume 274, ESA 2023, Complete Volume

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    LIPIcs, Volume 274, ESA 2023, Complete Volum

    Managing Smartphone Testbeds with SmartLab

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    The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. In this paper, we make three major contributions: First, we propose a comprehensive architecture, coined SmartLab1, for managing a cluster of both real and virtual smartphones that are either wired to a private cloud or connected over a wireless link. Second, we propose and describe a number of Android management optimizations (e.g., command pipelining, screen-capturing, file management), which can be useful to the community for building similar functionality into their systems. Third, we conduct extensive experiments and microbenchmarks to support our design choices providing qualitative evidence on the expected performance of each module comprising our architecture. This paper also overviews experiences of using SmartLab in a research-oriented setting and also ongoing and future development efforts

    LIPIcs, Volume 248, ISAAC 2022, Complete Volume

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    LIPIcs, Volume 248, ISAAC 2022, Complete Volum

    Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

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    The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios

    27th Annual European Symposium on Algorithms: ESA 2019, September 9-11, 2019, Munich/Garching, Germany

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    Aspects of the tourism market development within the European rural space

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    The paper makes an analysis of rural tourism market development with the presentation of the main players in the European rural tourism. The methodology used is based on the synthesis of information from articles and studies published in specialty journals, in Government documents as well as in other development strategies on tourism and rural space. The results of this scientific research study reconfirm that rural tourism promotion and development are based on the existing tourism potential and also on the involvement of governmental and non governmental institutions
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