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156. A roadmap to the introduction of pervasive information systems in healthcare

Author

Kitsios, Fotis, Papadopoulos, Thanos, Angelopoulos, Spyros, Kitsios, Fotis, Papadopoulos, Thanos, and Angelopoulos, Spyros

Abstract

Pervasive healthcare is an emerging research discipline, which focuses on the development of pervasive and ubiquitous computing technology for healthcare environments. Information and Communication Technologies have dramatically evolved during the last decade, laying a solid foundation for the future generation of Ubiquitous Internet access. As a result, current efforts in research and development in the areas of pervasive healthcare, promote the formation of inter-disciplinary international teams of experts, scientists, researchers and engineers to create a new generation of applications and technologies that will facilitate the fully automated information cyberspace systems. The authors discuss the current state-of-the-art in the world of Telecommunications and Internet Technologies as well as new technological trends in the Internet and Automation Industries, while promoting research and development in the interdisciplinary projects conducted by multinational teams worldwide. © 2011, IGI Global.

Published
2012

157. Parameterized Analysis of Online Steiner Tree Problems

Author

Spyros Angelopoulos, Angelopoulos, Spyros, Spyros Angelopoulos, and Angelopoulos, Spyros

Abstract

Steiner tree problems occupy a central place in both areas of approximation and on-line algorithms. Many variants have been studied from the point of view of competitive analysis, and for several of these variants tight bounds are known. However, in several cases, worst-case analysis is overly pessimistic, which fails to explain the relative performance of algorithms. We show how adaptive analysis can help resolve this problem. As case studies, we consider the Steiner tree problem in directed graphs, and the Priority Steiner tree problem.

Published
2009
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162. Emergence and Evolution of Digital Transformation: A Morphogenetic Approach.

Author

Struijk, Mylène, Angelopoulos, Spyros, and Ou, Carol Xiaojuan

Abstract

Digital transformation (DT) endeavors present high levels of failure due to their complexity, bringing to the fore the importance of better understanding how they emerge and unfold over time. To address that lacuna, we adopt a morphogenetic approach (MA) and draw upon institutional theory, as well as ten years of organizational documents and 60 interviews with employees of a multinational military organization. We uncover an emergent digital logic, which enables grasping organizational reality, pressures, appropriate behavior, and success in the digital age. Moreover, we identify four morphogenetic cycles, revealing that DT revolves around responses to institutional complexity that are dependent on interactions amongst culture, structure, and agency. We demonstrate that DT is shaped by dynamic organizational responses to institutional complexity as the digital logic emerges. Importantly, we show that the DT endeavor is initiated unconsciously before the organization starts making conscious, structural DT changes. Finally, we contribute to opening the black box of agency in dealing with institutional complexity and DT endeavors. Specifically, we identify different strategies over time that proponents of the emerging logic adopt to push the organization towards the new logic. [ABSTRACT FROM AUTHOR]

Published
2022
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165. The Node-Weighted Steiner Problem in Graphs of Restricted Node Weights.

Author

Arge, Lars, Freivalds, Rusins, and Angelopoulos, Spyros

Abstract

In this paper we study a variant of the Node-Weighted Steiner Tree problem in which the weights (costs) of vertices are restricted, in the sense that the ratio of the maximum node weight to the minimum node weight is bounded by a quantity α. This problem has applications in multicast routing where the cost of participating routers must be taken into consideration and the network is relatively homogenous in terms of the cost of the routers. We consider both online and offline versions of the problem. For the offline version we show an upper bound of O( min {logα, logk}) on the approximation ratio of deterministic algorithms (where k is the number of terminals). We also prove that the bound is tight unless P=NP. For the online version we show a tight bound of Θ( max { min {α, k}, logk }), which applies to both deterministic and randomized algorithms. We also show how to apply (and extend to node-weighted graphs) recent work of Alon et al. so as to obtain a randomized online algorithm with competitive ratio O(logm logk), where m is the number of the edges in the graph, independently of the value of α. All our bounds also hold for the Generalized Node-Weighted Steiner Problem, in which only connectivity between pairs of vertices must be guaranteed. [ABSTRACT FROM AUTHOR]

Published
2006
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166. On-Line Algorithms for Market Equilibria.

Author

Wang, Lusheng, Angelopoulos, Spyros, Sarma, Atish Das, Magen, Avner, and Viglas, Anastasios

Abstract

We consider a variation of the classical problem of finding prices which guarantee equilibrium in linear markets consisting of divisible goods and agents with money. Specifically, we consider on-line algorithms for this problem in which goods are considered on-line, and each good is assigned an irrevocable price. Since exact equilibria will not be found in such a setting, we appeal to the concept of approximate equilibrium defined in previous studies of the problem, to characterize the quality of our solutions. We consider both deterministic and randomized algorithms for finding approximate equilibria. We prove a tight bound on the performance of deterministic algorithms, and show that under certain natural conditions, randomized algorithms lead to market prices which are closer to equilibrium. [ABSTRACT FROM AUTHOR]

Published
2005
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167. Order-Preserving Transformations and Greedy-Like Algorithms.

Author

Persiano, Giuseppe, Solis-Oba, Roberto, and Angelopoulos, Spyros

Abstract

Borodin, Nielsen and Rackoff [5] proposed a framework for abstracting the main properties of greedy-like algorithms with emphasis on scheduling problems, and Davis and Impagliazzo [6] extended it so as to make it applicable to graph optimization problems. In this paper we propose a related model which places certain reasonable restrictions on the power of the greedy-like algorithm. Our goal is to define a model in which it is possible to filter out certain overly powerful algorithms, while still capturing a very rich class of greedy-like algorithms. We argue that this approach better motivates the lower-bound proofs and possibly yields better bounds. To illustrate the techniques involved we apply the model to the well-known problems of (complete) facility location and dominating set. Keywords: Priority algorithms, inapproximability results, facility location, dominating set. [ABSTRACT FROM AUTHOR]

Published
2005

168. Dynamic Competition Identification Through Consumers' Clickstream Data.

Author

Meihua Zuo, Xiaojuan Ou, Carol, Hongwei Liu, Zhouyang Liang, and Angelopoulos, Spyros

Abstract

Brands that use online marketplaces face challenges on identifying the market structure and analyzing their competitiveness. We address that lacuna by modeling online consumers' behavior using clickstream data and considering the interdependence of brands using network analysis. We draw on a dataset of 6,549,484 records over a period of 10 weeks from one of the biggest online marketplaces in China and employ spatial auto-regressive models and network structural properties of brands to predict sales. Our findings indicate that intra-brand competition is more intense than inter-brand one and is the main reason for the fluctuations of sales. Concurrently, we demonstrate the redistribution of market shares of related products after the firm adjusts the length of the production line, so as to provide a reference for how to adjust the length intra-brand. By exploring the relationship between the structural position in the network and brand sales, we show that the span of structural holes of a brand negatively influences sales, while betweenness and degree centrality has a positive impact on sales. Our study contributes to the better understanding of brand competition on online marketplaces and presents both theoretical and practical implications. We discuss the significance of our findings for brand competition on online marketplaces and platforms, while we draw an agenda for future research on the topic. [ABSTRACT FROM AUTHOR]

Published
2020
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169. Managing privacy, rights, and security in a digital economy

Author

Angelopoulos, Spyros, Mortier, Richard, Mcauley, Derek, Merali, Y, Price, Dominic, Department of Management, and Research Group: Information & Supply Chain Management

Abstract

We focus on the issues of managing Big Data within a Digital Economy, and address the asymmetrical distribution of power between the originators of data and the organizations that make use of that data. We propose a framework to overcome many of the challenges associated with storage, analysis, and integrity by taking a systemic perspective, shifting from a user-provider relationship to a more symbiotic one in which control over access to user data resides with the user. We present our framework, which combines the principles of Separation of Concerns and Distributed Computing, and discuss its implications as well as its limitations.

170. Small fish in a big pond: an architectural approach to users privacy, rights and security in the age of big data

Author

Angelopoulos, Spyros, McAuley, Derek, Merali, Yasmin, Mortier, Richard, Price, Dominic, Angelopoulos, Spyros, McAuley, Derek, Merali, Yasmin, Mortier, Richard, and Price, Dominic

Abstract

We focus on the challenges and issues associated with Big Data, and propose a novel architecture that uses the principles of Separation of Concerns and distributed computing to overcome many of the challenges associated with storage, analysis and integrity. We address the issue of asymmetrical distribution of power between the originators of data and the organizations and institutions that make use of that data by taking a systemic perspective to include both sides in our architectural design, shifting from a customer-provider relationship to a more symbiotic one in which control over access to customer data resides with the customer. We illustrate the affordances of the proposed architecture by describing its application in the domain of Social Networking Sites, where we furnish a mechanism to address problems of privacy and identity, and create the potential to open up online social networking to a richer set of possible applications.

171. Inter-social-networking: accounting for multiple identities

Author

Price, Dominic, McAuley, Derek, Mortier, Richard, Greenhalgh, Chris, Brown, Michael, Angelopoulos, Spyros, Price, Dominic, McAuley, Derek, Mortier, Richard, Greenhalgh, Chris, Brown, Michael, and Angelopoulos, Spyros

Abstract

We argue that the current approaches to online social networking give rise to numerous challenges regarding the management of the multiple facets of people’s digital identities within and around social networking sites (SNS). We propose an architecture for enabling people to better manage their SNS identities that is informed by the way the core Internet protocols developed to support interoperation of proprietary network protocols, and based on the idea of Separation of Concerns [1]. This does not require modification of existing services but is predicated on providing a connecting layer over them, both as a mechanism to address problems of privacy and identity, and to create opportunities to open up online social networking to a much richer set of possible interactions and applications.

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172. The expanding search ratio of a graph

Author

Ollinger, Nicolas, Vollmer, Heribert, Angelopoulos, Spyros, Dürr, Christoph, Lidbetter, Thomas, Ollinger, Nicolas, Vollmer, Heribert, Angelopoulos, Spyros, Dürr, Christoph, and Lidbetter, Thomas

Abstract

We study the problem of searching for a hidden target in an environment that is modeled by an edge-weighted graph. Most of the previous work on this problem considers the pathwise cost formulation, in which the cost incurred by the searcher is the overall time to locate the target, assuming that the searcher moves at unit speed. More recent work introduced the setting of expanding search in which the searcher incurs cost only upon visiting previously unexplored areas of the graph. Such a paradigm is useful in modeling problems in which the cost of re-exploration is negligible (such as coal mining). In our work we study algorithmic and computational issues of expanding search, for a variety of search environments including general graphs, trees and star-like graphs. In particular, we rely on the deterministic and randomized search ratio as the performance measures of search strategies, which were originally introduced by Koutsoupias and Papadimitriou [ICALP 1996] in the context of pathwise search. The search ratio is essentially the best competitive ratio among all possible strategies. Our main objective is to explore how the transition from pathwise to expanding search affects the competitive analysis, which has applications to optimization problems beyond the strict boundaries of search problems.

173. Small fish in a big pond: an architectural approach to users privacy, rights and security in the age of big data

Author

Angelopoulos, Spyros, McAuley, Derek, Merali, Yasmin, Mortier, Richard, Price, Dominic, Angelopoulos, Spyros, McAuley, Derek, Merali, Yasmin, Mortier, Richard, and Price, Dominic

Abstract

We focus on the challenges and issues associated with Big Data, and propose a novel architecture that uses the principles of Separation of Concerns and distributed computing to overcome many of the challenges associated with storage, analysis and integrity. We address the issue of asymmetrical distribution of power between the originators of data and the organizations and institutions that make use of that data by taking a systemic perspective to include both sides in our architectural design, shifting from a customer-provider relationship to a more symbiotic one in which control over access to customer data resides with the customer. We illustrate the affordances of the proposed architecture by describing its application in the domain of Social Networking Sites, where we furnish a mechanism to address problems of privacy and identity, and create the potential to open up online social networking to a richer set of possible applications.

174. Inter-social-networking: accounting for multiple identities

Author

Price, Dominic, McAuley, Derek, Mortier, Richard, Greenhalgh, Chris, Brown, Michael, Angelopoulos, Spyros, Price, Dominic, McAuley, Derek, Mortier, Richard, Greenhalgh, Chris, Brown, Michael, and Angelopoulos, Spyros

Abstract

We argue that the current approaches to online social networking give rise to numerous challenges regarding the management of the multiple facets of people’s digital identities within and around social networking sites (SNS). We propose an architecture for enabling people to better manage their SNS identities that is informed by the way the core Internet protocols developed to support interoperation of proprietary network protocols, and based on the idea of Separation of Concerns [1]. This does not require modification of existing services but is predicated on providing a connecting layer over them, both as a mechanism to address problems of privacy and identity, and to create opportunities to open up online social networking to a much richer set of possible interactions and applications.

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175. Small fish in a big pond: an architectural approach to users privacy, rights and security in the age of big data

Author

Angelopoulos, Spyros, McAuley, Derek, Merali, Yasmin, Mortier, Richard, Price, Dominic, Angelopoulos, Spyros, McAuley, Derek, Merali, Yasmin, Mortier, Richard, and Price, Dominic

Abstract

We focus on the challenges and issues associated with Big Data, and propose a novel architecture that uses the principles of Separation of Concerns and distributed computing to overcome many of the challenges associated with storage, analysis and integrity. We address the issue of asymmetrical distribution of power between the originators of data and the organizations and institutions that make use of that data by taking a systemic perspective to include both sides in our architectural design, shifting from a customer-provider relationship to a more symbiotic one in which control over access to customer data resides with the customer. We illustrate the affordances of the proposed architecture by describing its application in the domain of Social Networking Sites, where we furnish a mechanism to address problems of privacy and identity, and create the potential to open up online social networking to a richer set of possible applications.

176. Inter-social-networking: accounting for multiple identities

Author

Price, Dominic, McAuley, Derek, Mortier, Richard, Greenhalgh, Chris, Brown, Michael, Angelopoulos, Spyros, Price, Dominic, McAuley, Derek, Mortier, Richard, Greenhalgh, Chris, Brown, Michael, and Angelopoulos, Spyros

Abstract

We argue that the current approaches to online social networking give rise to numerous challenges regarding the management of the multiple facets of people’s digital identities within and around social networking sites (SNS). We propose an architecture for enabling people to better manage their SNS identities that is informed by the way the core Internet protocols developed to support interoperation of proprietary network protocols, and based on the idea of Separation of Concerns [1]. This does not require modification of existing services but is predicated on providing a connecting layer over them, both as a mechanism to address problems of privacy and identity, and to create opportunities to open up online social networking to a much richer set of possible interactions and applications.

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177. Small fish in a big pond: an architectural approach to users privacy, rights and security in the age of big data

Author

Angelopoulos, Spyros, McAuley, Derek, Merali, Yasmin, Mortier, Richard, Price, Dominic, Angelopoulos, Spyros, McAuley, Derek, Merali, Yasmin, Mortier, Richard, and Price, Dominic

Abstract

We focus on the challenges and issues associated with Big Data, and propose a novel architecture that uses the principles of Separation of Concerns and distributed computing to overcome many of the challenges associated with storage, analysis and integrity. We address the issue of asymmetrical distribution of power between the originators of data and the organizations and institutions that make use of that data by taking a systemic perspective to include both sides in our architectural design, shifting from a customer-provider relationship to a more symbiotic one in which control over access to customer data resides with the customer. We illustrate the affordances of the proposed architecture by describing its application in the domain of Social Networking Sites, where we furnish a mechanism to address problems of privacy and identity, and create the potential to open up online social networking to a richer set of possible applications.

178. Inter-social-networking: accounting for multiple identities

Author

Price, Dominic, McAuley, Derek, Mortier, Richard, Greenhalgh, Chris, Brown, Michael, Angelopoulos, Spyros, Price, Dominic, McAuley, Derek, Mortier, Richard, Greenhalgh, Chris, Brown, Michael, and Angelopoulos, Spyros

Abstract

We argue that the current approaches to online social networking give rise to numerous challenges regarding the management of the multiple facets of people’s digital identities within and around social networking sites (SNS). We propose an architecture for enabling people to better manage their SNS identities that is informed by the way the core Internet protocols developed to support interoperation of proprietary network protocols, and based on the idea of Separation of Concerns [1]. This does not require modification of existing services but is predicated on providing a connecting layer over them, both as a mechanism to address problems of privacy and identity, and to create opportunities to open up online social networking to a much richer set of possible interactions and applications.

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179. Unfolding the Transcendence of Boundaries Across the Digital and Physical.

Author

Angelopoulos, Spyros and Merali, Yasmin

Abstract

We conduct a data-driven exploration of the way in which technological affordances are implicated in the emergence of collective practices and behaviors that underpin the macro-level phenomenology of digitally-enabled communities. We view such communities essentially as digitally-enabled social networks, and for our study we created, populated, and tracked for 18 months an online community of cigar smokers. In this paper, we introduce a novel methodological approach that combines longitudinal social network analysis with content analysis to yield a nuanced exposition of the micro- and meso- level structures, dynamics and practices underpinning emergent and persistent macro-level community phenomenology. We identified six distinctive types of activities entailing interactions that transcend offline/online boundaries, associated with practices that combined symbolic and material artifacts to generate collective social and economic value. Our findings extend extant knowledge of community dynamics, collaborative practices, and value-creation processes on online communities to move beyond traditional views of online phenomena. [ABSTRACT FROM AUTHOR]

Published
2017
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180. Exploring social processes on online communities : emergence and evolution of social networks

Author

Angelopoulos, Spyros

Subjects
658, HM Sociology
Abstract

The thesis is focused on the possibilities that exist for crossing or even transcending the boundary between existence in the real and virtual worlds, and it presents the findings of a longitudinal study of an online community of cigar smokers, which was created for the needs of the study, tracing the interactions of its participants over a period of eighteen months. The internet enables the formation of online communities that provide unprecedented opportunities for communication across geographic, political and economic divides, and reach across barriers of distance, time and culture. Such communities provide a space for people to come together based on existing friendships, common interests, their work, and a variety of other factors. The study is aligned with the literature that views online communities as social networks, and such a way of thinking enables us to understand the relationship between structure and dynamics, and reveals the different roles of the participants, their relationships, as well as the structure of the social system that underpin the observed development of online communities. Network analysts suggest that offline relations affect the online interaction of participants; the ways in which that occurs, however, is still left unanswered. Although the literature suggests the need for more longitudinal studies on the role of online communities in creating novel interaction channels for both networks and individuals, there are very few to date. Moreover, the literature has mainly focused on the structural specifications of networks, and has paid scant attention to the content of the conversations that connected individuals are having. Hence, a longitudinal study with a focus on communicative processes is needed, to provide a focus on networks, people, and processes. To elucidate the understanding of offline interactions, the study explores an online community of cigar smokers, and traces such interactions identified in the content. The online community was created for the needs of the study, and populated through an online invitation system to track the initial relations among participants. The novel methodological approach of the study combines social network analysis with content analysis to generate a more nuanced account of the emergence of roles and relationships associated with recorded activities and observed structural features of the social networks, and explore the relationship between online and offline interactions. The study identified six distinctive technology-driven social trends that affect the emergence and evolution of networks among the participants. The distinctive patterns of interaction that persist over the course of the study are associated with a mix of behaviors that include play, trading and gifting, and entail the exchange or flow of informational and material objects. The findings of the study reveal that the participants of the online community used metaphors, puns, words from the everyday life repertoire, as well as the coining of new words, in order to communicate regarding such interactions. The diversity of activities across the community, and the flow of information, cigars, and money demonstrate the potential for complex, multi-faceted socioeconomic spaces that bridge the divide between virtual and embodied space, informational and material goods, and social and economic transactions. Moreover, the findings of the study shows that the offline interactions among the participants of the online community gave rise to a dense network of a homogenous population, with the properties of a scale free network, and of a small world with three degrees of separation. The interactions among the participants were highly reciprocated and reinforced, contributing to the growth of the network over time, and the tendency of participants to connect with friends of friends is equally spread in the network and not affected by prominence. There is a positive and statistically significant rich-club effect in the network, showing that the prominent participants do not compete with each other for status, rather they tend to interact with each other. The growth of the network can be divided into two periods: an initial accelerated growth, and an equilibrium period of homogenization of the population. During the initial accelerated phase, the backbone of the network is established, which contributes to the stability in shortest-path based metrics over time, and the overall density of the network. The findings suggest that we should treat with caution conclusions that relate differences in status to differences in network position. Although hubs in a network can control the diffusion of recourses across the entire community, the unstable nature of such positions suggests that the participants do not hold them indefinitely, and these positions offer only a temporary advantage to those who posses them. Furthermore, it is unclear to what extent individuals can strategically manipulate their positions in a large network, even if that is their intention. The findings of the study illustrate the value of combining network analysis and content analysis to understand the evolving structure of online communities and their offline extensions. The study provides academics with new insights regarding the interactions of participants of online communities, and open new avenues for future research on the topic. Bridging work remains at the core of making sense of social experiences online, and the findings of the study contribute to the literature on online communities by responding to calls for more studies to make sense of the relationship between the online and offline activities. Moreover, this study contributes to the broader Information Systems literature, and more specifically to the field of Computer-Mediated Communication, by elucidating the evolving social interactions amongst participants of passion-centric online communities. When it comes to practitioners, the findings of the study here can provide the managers of online communities with novel insights on how to study and understand the communities they manage, identify opportunities or problems, and deliver policies and interventions in networked forms. Furthermore, the findings of this study can enable the managers of online communities to think of innovative ways to enable the participants to engage in offline interactions, without the fear that such interactions will negate the sustainability of the online community, while by enabling them to engage in such interactions, they can build more robust and successful online communities.

Published
2013

182. Online Bin Packing with Predictions

Author

Spyros Angelopoulos, Shahin Kamali, Kimia Shadkami, Centre National de la Recherche Scientifique (CNRS), Recherche Opérationnelle (RO), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Angelopoulos, Spyros

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, Computer Science - Machine Learning, I.2.6, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], F.2.0, [INFO] Computer Science [cs], Machine Learning (cs.LG), [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 68T05, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), [INFO]Computer Science [cs]
Abstract

Bin packing is a classic optimization problem with a wide range of applications from load balancing in networks to supply chain management. In this work we study the online variant of the problem, in which a sequence of items of various sizes must be placed into a minimum number of bins of uniform capacity. The online algorithm is enhanced with a (potentially erroneous) prediction concerning the frequency of item sizes in the sequence. We design and analyze online algorithms with efficient tradeoffs between consistency (i.e., the competitive ratio assuming no prediction error) and robustness (i.e., the competitive ratio under adversarial error), and whose performance degrades gently as a function of the prediction error. This is the first theoretical study of online bin packing in the realistic setting of erroneous predictions, as well as the first experimental study in the setting in which the input is generated according to both static and evolving distributions. Previous work on this problem has only addressed the extreme cases with respect to the prediction error, has relied on overly powerful and error-free prediction oracles, and has focused on experimental evaluation based on static input distributions., 28 pages, 4 figures

Published
2021

183. Contract Scheduling With Predictions

Author

Spyros Angelopoulos, Shahin Kamali, Recherche Opérationnelle (RO), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of Manitoba [Winnipeg], Publications, Lip6, and Angelopoulos, Spyros

Subjects
FOS: Computer and information sciences, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], Computer Science - Artificial Intelligence, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], General Medicine, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], [INFO] Computer Science [cs], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Artificial Intelligence (cs.AI), Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), [INFO]Computer Science [cs], Computer Science::Operating Systems
Abstract

International audience; Contract scheduling is a general technique that allows to design a system with interruptible capabilities, given an algorithm that is not necessarily interruptible. Previous work on this topic has largely assumed that the interruption is a worst-case deadline that is unknown to the scheduler. In this work, we study the setting in which there is a potentially erroneous prediction concerning the interruption. Specifically, we consider the setting in which the prediction describes the time that the interruption occurs, as well as the setting in which the prediction is obtained as a response to a single or multiple binary queries. For both settings, we investigate tradeoffs between the robustness (i.e., the worst-case performance assuming adversarial prediction) and the consistency (i.e, the performance assuming that the prediction is error-free), both from the side of positive and negative results.

Published
2020

184. Further Connections Between Contract-Scheduling and Ray-Searching Problems

Author

Spyros Angelopoulos, Recherche Opérationnelle (RO), Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Angelopoulos, Spyros

Subjects
FOS: Computer and information sciences, Schedule, Optimization problem, Theoretical computer science, Computer science, Computer Science - Artificial Intelligence, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [MATH] Mathematics [math], 0102 computer and information sciences, 02 engineering and technology, [INFO] Computer Science [cs], Management Science and Operations Research, 01 natural sciences, First class, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Scheduling (computing), Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, Redundancy (engineering), [INFO]Computer Science [cs], [MATH]Mathematics [math], Class (computer programming), General Engineering, Probabilistic logic, Artificial Intelligence (cs.AI), 010201 computation theory & mathematics, Resource allocation, 020201 artificial intelligence & image processing, Software
Abstract

This paper addresses two classes of different, yet interrelated optimization problems. The first class of problems involves a robot that must locate a hidden target in an environment that consists of a set of concurrent rays. The second class pertains to the design of interruptible algorithms by means of a schedule of contract algorithms. We study several variants of these families of problems, such as searching and scheduling with probabilistic considerations, redundancy and fault-tolerance issues, randomized strategies, and trade-offs between performance and preemptions. For many of these problems we present the first known results that apply to multi-ray and multi-problem domains. Our objective is to demonstrate that several well-motivated settings can be addressed using the same underlying approach., Full version of conference paper, to appear in Proceedings of IJCAI 2015

Published
2015

185. The impact of intersectional racial and gender biases on minority female leadership over two centuries.

Author

Pogrebna G, Angelopoulos S, Motsi-Omoijiade I, Kharlamov A, and Tkachenko N

Subjects
Humans, Female, United States, Sexism, Racial Groups, Minority Groups, Leadership, Intersectional Framework
Abstract

This study scrutinizes the enduring effects of racial and gender biases that contribute to the consistent underrepresentation of minority women in leadership roles within American private, public, and third sector organizations. We adopt a behavioural data science approach, merging psychological schema theory with sociological intersectionality theory, to evaluate the enduring implications of these biases on female leadership development using mixed methods including machine learning and econometric analysis. Our examination is concentrated on Black female leaders, employing an extensive analysis of leadership rhetoric data spanning 200 years across the aforementioned sectors. We shed light on the continued scarcity of minority female representation in leadership roles, highlighting the role of intersectionality dynamics. Despite Black female leaders frequently embracing higher risks to counter intersectional invisibility compared to their White counterparts, their aspirations are not realized and problems not solved generation after generation, forcing Black female leaders to concentrate on the same issues for dozens and, sometimes, hundreds of years. Our findings suggest that the compound influence of racial and gender biases hinders the advancement of minority female leadership by perpetuating stereotypical behavioral schemas, leading to persistent discriminatory outcomes. We argue for the necessity of organizations to initiate a cultural transformation that fosters positive experiences for future generations of female leaders, recommending a shift in focus from improving outcomes for specific groups to creating an inclusive leadership culture., (© 2024. The Author(s).)

Published
2024
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186. Operationalising fairness in medical AI adoption: detection of early Alzheimer's disease with 2D CNN.

Author

Heising L and Angelopoulos S

Subjects
Artificial Intelligence, Humans, Magnetic Resonance Imaging methods, Neural Networks, Computer, Alzheimer Disease diagnostic imaging, Cognitive Dysfunction diagnosis
Abstract

Objectives: To operationalise fairness in the adoption of medical artificial intelligence (AI) algorithms in terms of access to computational resources, the proposed approach is based on a two-dimensional (2D) convolutional neural networks (CNN), which provides a faster, cheaper and accurate-enough detection of early Alzheimer's disease (AD) and mild cognitive impairment (MCI), without the need for use of large training data sets or costly high-performance computing (HPC) infrastructures., Methods: The standardised Alzheimer's Disease Neuroimaging Initiative (ADNI) data sets are used for the proposed model, with additional skull stripping, using the Brain Extraction Tool V.2approach. The 2D CNN architecture is based on LeNet-5, the Leaky Rectified Linear Unit activation function and a Sigmoid function were used, and batch normalisation was added after every convolutional layer to stabilise the learning process. The model was optimised by manually tuning all its hyperparameters., Results: The model was evaluated in terms of accuracy, recall, precision and f1-score. The results demonstrate that the model predicted MCI with an accuracy of 0.735, passing the random guessing baseline of 0.521 and predicted AD with an accuracy of 0.837, passing the random guessing baseline of 0.536., Discussion: The proposed approach can assist clinicians in the early diagnosis of AD and MCI, with high-enough accuracy, based on relatively smaller data sets, and without the need of HPC infrastructures. Such an approach can alleviate disparities and operationalise fairness in the adoption of medical algorithms., Conclusion: Medical AI algorithms should not be focused solely on accuracy but should also be evaluated with respect to how they might impact disparities and operationalise fairness in their adoption., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Published
2022
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