389 research outputs found

    Preventing Discriminatory Decision-making in Evolving Data Streams

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    Bias in machine learning has rightly received significant attention over the last decade. However, most fair machine learning (fair-ML) work to address bias in decision-making systems has focused solely on the offline setting. Despite the wide prevalence of online systems in the real world, work on identifying and correcting bias in the online setting is severely lacking. The unique challenges of the online environment make addressing bias more difficult than in the offline setting. First, Streaming Machine Learning (SML) algorithms must deal with the constantly evolving real-time data stream. Second, they need to adapt to changing data distributions (concept drift) to make accurate predictions on new incoming data. Adding fairness constraints to this already complicated task is not straightforward. In this work, we focus on the challenges of achieving fairness in biased data streams while accounting for the presence of concept drift, accessing one sample at a time. We present Fair Sampling over Stream (FS2FS^2), a novel fair rebalancing approach capable of being integrated with SML classification algorithms. Furthermore, we devise the first unified performance-fairness metric, Fairness Bonded Utility (FBU), to evaluate and compare the trade-off between performance and fairness of different bias mitigation methods efficiently. FBU simplifies the comparison of fairness-performance trade-offs of multiple techniques through one unified and intuitive evaluation, allowing model designers to easily choose a technique. Overall, extensive evaluations show our measures surpass those of other fair online techniques previously reported in the literature

    The Public Performance Of Sanctions In Insolvency Cases: The Dark, Humiliating, And Ridiculous Side Of The Law Of Debt In The Italian Experience. A Historical Overview Of Shaming Practices

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    This study provides a diachronic comparative overview of how the law of debt has been applied by certain institutions in Italy. Specifically, it offers historical and comparative insights into the public performance of sanctions for insolvency through shaming and customary practices in Roman Imperial Law, in the Middle Ages, and in later periods. The first part of the essay focuses on the Roman bonorum cessio culo nudo super lapidem and on the medieval customary institution called pietra della vergogna (stone of shame), which originates from the Roman model. The second part of the essay analyzes the social function of the zecca and the pittima Veneziana during the Republic of Venice, and of the practice of lu soldate a castighe (no translation is possible). The author uses a functionalist approach to apply some arguments and concepts from the current context to this historical analysis of ancient institutions that we would now consider ridiculous. The article shows that the customary norms that play a crucial regulatory role in online interactions today can also be applied to the public square in the past. One of these tools is shaming. As is the case in contemporary online settings, in the public square in historic periods, shaming practices were used to enforce the rules of civility in a given community. Such practices can be seen as virtuous when they are intended for use as a tool to pursue positive change in forces entrenched in the culture, and thus to address social wrongs considered outside the reach of the law, or to address human rights abuses

    A survey on machine learning for recurring concept drifting data streams

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    The problem of concept drift has gained a lot of attention in recent years. This aspect is key in many domains exhibiting non-stationary as well as cyclic patterns and structural breaks affecting their generative processes. In this survey, we review the relevant literature to deal with regime changes in the behaviour of continuous data streams. The study starts with a general introduction to the field of data stream learning, describing recent works on passive or active mechanisms to adapt or detect concept drifts, frequent challenges in this area, and related performance metrics. Then, different supervised and non-supervised approaches such as online ensembles, meta-learning and model-based clustering that can be used to deal with seasonalities in a data stream are covered. The aim is to point out new research trends and give future research directions on the usage of machine learning techniques for data streams which can help in the event of shifts and recurrences in continuous learning scenarios in near real-time

    Machine Learning Algorithm for the Scansion of Old Saxon Poetry

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    Several scholars designed tools to perform the automatic scansion of poetry in many languages, but none of these tools deal with Old Saxon or Old English. This project aims to be a first attempt to create a tool for these languages. We implemented a Bidirectional Long Short-Term Memory (BiLSTM) model to perform the automatic scansion of Old Saxon and Old English poems. Since this model uses supervised learning, we manually annotated the Heliand manuscript, and we used the resulting corpus as labeled dataset to train the model. The evaluation of the performance of the algorithm reached a 97% for the accuracy and a 99% of weighted average for precision, recall and F1 Score. In addition, we tested the model with some verses from the Old Saxon Genesis and some from The Battle of Brunanburh, and we observed that the model predicted almost all Old Saxon metrical patterns correctly misclassified the majority of the Old English input verses

    The Negative Existential Cycle

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    In 1991, William Croft suggested that negative existentials (typically lexical expressions that mean ‘not exist, not have’) are one possible source for negation markers and gave his hypothesis the name Negative Existential Cycle (NEC). It is a variationist model based on cross-linguistic data. For a good twenty years following its formulation, it was cited at face-value without ever having been tested by (historical)-comparative data. Over the last decade, Ljuba Veselinova has worked on testing the model in a comparative perspective, and this edited volume further expands on her work. The collection presented here features detailed studies of several language families such as Bantu, Chadic and Indo-European. A number of articles focus on the micro-variation and attested historical developments within smaller groups and clusters such as Arabic, Mandarin and Cantonese, and Nanaic. Finally, variation and historical developments in specific languages are discussed for Ancient Hebrew, Ancient Egyptian, Moksha-Mordvin (Uralic), Bashkir (Turkic), Kalmyk (Mongolic), three Pama-Nyungan languages, O’dam (Southern Uto-Aztecan) and Tacana (Takanan, Amazonian Bolivia). The book is concluded by two chapters devoted to modeling cyclical processes in language change from different theoretical perspectives. Key notions discussed throughout the book include affirmative and negative existential constructions, the expansion of the latter into verbal negation, and subsequently from more specific to more general markers of negation. Nominalizations as well as the uses of negative existentials as standalone negative answers figure among the most frequent pathways whereby negative existentials evolve as general negation markers. The operation of the Negative Existential Cycle appears partly genealogically conditioned, as the cycle is found to iterate regularly within some families but never starts in others, as is the case in Bantu. In addition, other special negation markers such as nominal negators are found to undergo similar processes, i.e. they expand into the verbal domain and thereby develop into more general negation markers. The book provides rich information on a specific path of the evolution of negation, on cyclical processes in language change, and it show-cases the historical-comparative method in a modern setting

    International Academic Symposium of Social Science 2022

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    This conference proceedings gathers work and research presented at the International Academic Symposium of Social Science 2022 (IASSC2022) held on July 3, 2022, in Kota Bharu, Kelantan, Malaysia. The conference was jointly organized by the Faculty of Information Management of Universiti Teknologi MARA Kelantan Branch, Malaysia; University of Malaya, Malaysia; Universitas Pembangunan Nasional Veteran Jakarta, Indonesia; Universitas Ngudi Waluyo, Indonesia; Camarines Sur Polytechnic Colleges, Philippines; and UCSI University, Malaysia. Featuring experienced keynote speakers from Malaysia, Australia, and England, this proceeding provides an opportunity for researchers, postgraduate students, and industry practitioners to gain knowledge and understanding of advanced topics concerning digital transformations in the perspective of the social sciences and information systems, focusing on issues, challenges, impacts, and theoretical foundations. This conference proceedings will assist in shaping the future of the academy and industry by compiling state-of-the-art works and future trends in the digital transformation of the social sciences and the field of information systems. It is also considered an interactive platform that enables academicians, practitioners and students from various institutions and industries to collaborate

    Operatic Pasticcios in 18th-Century Europe

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    In Early Modern times, techniques of assembling, compiling and arranging pre-existing material were part of the established working methods in many arts. In the world of 18th-century opera, such practices ensured that operas could become a commercial success because the substitution or compilation of arias fitting the singer's abilities proved the best recipe for fulfilling the expectations of audiences. Known as »pasticcios« since the 18th-century, these operas have long been considered inferior patchwork. The volume collects essays that reconsider the pasticcio, contextualize it, define its preconditions, look at its material aspects and uncover its aesthetical principles

    Proc. 33. Workshop Computational Intelligence, Berlin, 23.-24.11.2023

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    Dieser Tagungsband enthält die Beiträge des 33. Workshops „Computational Intelligence“ der vom 23.11. – 24.11.2023 in Berlin stattfindet. Die Schwerpunkte sind Methoden, Anwendungen und Tools für ° Fuzzy-Systeme, ° Künstliche Neuronale Netze, ° Evolutionäre Algorithmen und ° Data-Mining-Verfahren sowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen.The workshop proceedings contain the contributions of the 33rd workshop "Computational Intelligence" which will take place from 23.11. - 24.11.2023 in Berlin. The focus is on methods, applications and tools for ° Fuzzy systems, ° Artificial Neural Networks, ° Evolutionary algorithms and ° Data mining methods as well as the comparison of methods on the basis of industrial and benchmark problems

    Changing Priorities. 3rd VIBRArch

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    In order to warrant a good present and future for people around the planet and to safe the care of the planet itself, research in architecture has to release all its potential. Therefore, the aims of the 3rd Valencia International Biennial of Research in Architecture are: - To focus on the most relevant needs of humanity and the planet and what architectural research can do for solving them. - To assess the evolution of architectural research in traditionally matters of interest and the current state of these popular and widespread topics. - To deepen in the current state and findings of architectural research on subjects akin to post-capitalism and frequently related to equal opportunities and the universal right to personal development and happiness. - To showcase all kinds of research related to the new and holistic concept of sustainability and to climate emergency. - To place in the spotlight those ongoing works or available proposals developed by architectural researchers in order to combat the effects of the COVID-19 pandemic. - To underline the capacity of architectural research to develop resiliency and abilities to adapt itself to changing priorities. - To highlight architecture's multidisciplinarity as a melting pot of multiple approaches, points of view and expertise. - To open new perspectives for architectural research by promoting the development of multidisciplinary and inter-university networks and research groups. For all that, the 3rd Valencia International Biennial of Research in Architecture is open not only to architects, but also for any academic, practitioner, professional or student with a determination to develop research in architecture or neighboring fields.Cabrera Fausto, I. (2023). Changing Priorities. 3rd VIBRArch. Editorial Universitat Politècnica de València. https://doi.org/10.4995/VIBRArch2022.2022.1686
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