Готові списки джерел за темами / Fairness constraints

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Автор: Grafiati

Опубліковано: 6 вересня 2023

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Статті в журналах з теми "Fairness constraints"

Detassis, Fabrizio, Michele Lombardi, and Michela Milano. "Teaching the Old Dog New Tricks: Supervised Learning with Constraints." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 5 (May 18, 2021): 3742–49. http://dx.doi.org/10.1609/aaai.v35i5.16491.

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Adding constraint support in Machine Learning has the potential to address outstanding issues in data-driven AI systems, such as safety and fairness. Existing approaches typically apply constrained optimization techniques to ML training, enforce constraint satisfaction by adjusting the model design, or use constraints to correct the output. Here, we investigate a different, complementary, strategy based on "teaching" constraint satisfaction to a supervised ML method via the direct use of a state-of-the-art constraint solver: this enables taking advantage of decades of research on constrained optimization with limited effort. In practice, we use a decomposition scheme alternating master steps (in charge of enforcing the constraints) and learner steps (where any supervised ML model and training algorithm can be employed). The process leads to approximate constraint satisfaction in general, and convergence properties are difficult to establish; despite this fact, we found empirically that even a naive setup of our approach performs well on ML tasks with fairness constraints, and on classical datasets with synthetic constraints.

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Ben-Porat, Omer, Fedor Sandomirskiy, and Moshe Tennenholtz. "Protecting the Protected Group: Circumventing Harmful Fairness." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 6 (May 18, 2021): 5176–84. http://dx.doi.org/10.1609/aaai.v35i6.16654.

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The recent literature on fair Machine Learning manifests that the choice of fairness constraints must be driven by the utilities of the population. However, virtually all previous work makes the unrealistic assumption that the exact underlying utilities of the population (representing private tastes of individuals) are known to the regulator that imposes the fairness constraint. In this paper we initiate the discussion of the \emph{mismatch}, the unavoidable difference between the underlying utilities of the population and the utilities assumed by the regulator. We demonstrate that the mismatch can make the disadvantaged protected group worse off after imposing the fairness constraint and provide tools to design fairness constraints that help the disadvantaged group despite the mismatch.

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Li, Fengjiao, Jia Liu, and Bo Ji. "Combinatorial Sleeping Bandits With Fairness Constraints." IEEE Transactions on Network Science and Engineering 7, no. 3 (July 1, 2020): 1799–813. http://dx.doi.org/10.1109/tnse.2019.2954310.

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Pi, Jiancai. "Fairness compatibility constraints and collective actions." Frontiers of Economics in China 2, no. 4 (October 2007): 644–52. http://dx.doi.org/10.1007/s11459-007-0033-x.

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Vukadinović, Vladimir, and Gunnar Karlsson. "Multicast scheduling with resource fairness constraints." Wireless Networks 15, no. 5 (December 19, 2007): 571–83. http://dx.doi.org/10.1007/s11276-007-0085-y.

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Wang, Xiao Fei, Xi Zhang, Yue Bing Chen, Lei Zhang, and Chao Jing Tang. "Spectrum Assignment Algorithm Based on Clonal Selection in Cognitive Radio Networks." Advanced Materials Research 457-458 (January 2012): 931–39. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.931.

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An improved-immune-clonal-selection based spectrum assignment algorithm (IICSA) in cognitive radio networks is proposed, combing graph theory and immune optimization. It uses constraint satisfaction operation to make encoded antibody population satisfy constraints, and realizes the global optimization. The random-constraint satisfaction operator and fair-constraint satisfaction operator are designed to guarantee efficiency and fairness, respectively. Simulations are performed for performance comparison between the IICSA and the color-sensitive graph coloring algorithm. The results indicate that the proposed algorithm increases network utilization, and efficiently improves the fairness.

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Piron, Robert, and Luis Fernandez. "Are fairness constraints on profit-seeking important?" Journal of Economic Psychology 16, no. 1 (March 1995): 73–96. http://dx.doi.org/10.1016/0167-4870(94)00037-b.

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Zheng, Jiping, Yuan Ma, Wei Ma, Yanhao Wang, and Xiaoyang Wang. "Happiness maximizing sets under group fairness constraints." Proceedings of the VLDB Endowment 16, no. 2 (October 2022): 291–303. http://dx.doi.org/10.14778/3565816.3565830.

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Finding a happiness maximizing set (HMS) from a database, i.e., selecting a small subset of tuples that preserves the best score with respect to any nonnegative linear utility function, is an important problem in multi-criteria decision-making. When an HMS is extracted from a set of individuals to assist data-driven algorithmic decisions such as hiring and admission, it is crucial to ensure that the HMS can fairly represent different groups of candidates without bias and discrimination. However, although the HMS problem was extensively studied in the database community, existing algorithms do not take group fairness into account and may provide solutions that under-represent some groups. In this paper, we propose and investigate a fair variant of HMS (FairHMS) that not only maximizes the minimum happiness ratio but also guarantees that the number of tuples chosen from each group falls within predefined lower and upper bounds. Similar to the vanilla HMS problem, we show that FairHMS is NP-hard in three and higher dimensions. Therefore, we first propose an exact interval cover-based algorithm called IntCov for FairHMS on two-dimensional databases. Then, we propose a bicriteria approximation algorithm called BiGreedy for FairHMS on multi-dimensional databases by transforming it into a submodular maximization problem under a matroid constraint. We also design an adaptive sampling strategy to improve the practical efficiency of BiGreedy. Extensive experiments on real-world and synthetic datasets confirm the efficacy and efficiency of our proposal.

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Heaton, Stephen. "FINALITY OR FAIRNESS?" Cambridge Law Journal 73, no. 3 (November 2014): 477–80. http://dx.doi.org/10.1017/s0008197314000919.

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THE finality of proceedings, resource constraints, a presumption of guilt, and the existence of the Criminal Cases Review Commission (“CCRC”) all combine to outweigh the principle of fairness for a convicted individual. Such was the stark conclusion of the Supreme Court in dismissing Kevin Nunn's application to force prosecution authorities to grant access to material which he believed would help him get his conviction quashed: R. (Nunn) v Chief Constable of Suffolk Constabulary [2014] UKSC 37, [2014] 3 W.L.R. 77.

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Tan, Xianghua, Shasha Wang, Weili Zeng, and Zhibin Quan. "A Collaborative Optimization Method of Flight Slots Considering Fairness Among Airports." Mathematical Problems in Engineering 2022 (September 10, 2022): 1–18. http://dx.doi.org/10.1155/2022/1418911.

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With the rapid development of civil aviation transportation, an increasing number of airport groups are formed. However, the existing literature on fairness mostly focuses on the fairness among airlines. There is no research on the realization of scheduling fairness among airports with overlapping resources in the airport group. The goal of this paper is to comprehensively consider efficiency and fairness in slot scheduling, where fairness should include both interairline and interairport fairness. Subsequently, we developed a collaborative optimization model for airport group that takes into account the above three objectives and then uses the ε-constraint method to solve it. In addition to considering the basic operational constraints of the airport, the model also sets different adjustment boundaries to achieve the scheduling priorities specified by IATA. Applying the model to the Yangtze River Delta airport group, the results show that improved flight schedules can significantly reduce flight congestion, and a relatively fair scheduling result can be obtained by weighing airlines’ fairness and airports’ fairness. The model can improve the transparency of slot scheduling decisions and can be used as an auxiliary tool to help make slot scheduling decisions.

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Дисертації з теми "Fairness constraints"

Chandramouli, Shyam Sundar. "Network Resource Allocation Under Fairness Constraints." Thesis, 2014. https://doi.org/10.7916/D8S46Q3V.

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This work considers the basic problem of allocating resources among a group of agents in a network, when the agents are equipped with single-peaked preferences over their assignments. This generalizes the classical claims problem, which concerns the division of an estate's liquidation value when the total claim on it exceeds this value. The claims problem also models the problem of rationing a single commodity, or the problem of dividing the cost of a public project among the people it serves, or the problem of apportioning taxes. A key consideration in this classical literature is equity: the good (or the ``bad,'' in the case of apportioning taxes or costs) should be distributed as fairly as possible. The main contribution of this dissertation is a comprehensive treatment of a generalization of this classical rationing problem to a network setting. Bochet et al. recently introduced a generalization of the classical rationing problem to the network setting. For this problem they designed an allocation mechanism---the egalitarian mechanism---that is Pareto optimal, envy free and strategyproof. In chapter 2, it is shown that the egalitarian mechanism is in fact group strategyproof, implying that no coalition of agents can collectively misreport their information to obtain a (weakly) better allocation for themselves. Further, a complete characterization of the set of all group strategyproof mechanisms is obtained. The egalitarian mechanism satisfies many attractive properties, but fails consistency, an important property in the literature on rationing problems. It is shown in chapter 3 that no Pareto optimal mechanism can be envy-free and consistent. Chapter 3 is devoted to the edge-fair mechanism that is Pareto optimal, group strategyproof, and consistent. In a related model where the agents are located on the edges of the graph rather than the nodes, the edge-fair rule is shown to be envy-free, group strategyproof, and consistent. Chapter 4 extends the egalitarian mechanism to the problem of finding an optimal exchange in non-bipartite networks. The results vary depending on whether the commodity being exchanged is divisible or indivisible. For the latter case, it is shown that no efficient mechanism can be strategyproof, and that the egalitarian mechanism is Pareto optimal and envy-free. Chapter 5 generalizes recent work on finding stable and balanced allocations in graphs with unit capacities and unit weights to more general networks. The existence of a stable and balanced allocation is established by a transformation to an equivalent unit capacity network.

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Syu, Wun-Hao, and 徐文壕. "Maximizing Sum Capacity with Fairness Constraints in Multiuser OFDM Systems." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/54942351988603148574.

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碩士
國立中正大學
通訊工程研究所
95
Multiuser orthogonal frequency division multiplexing (Multiuser OFDM) is a promising technique for achieving high downlink capacities in future cellular and wireless local area network (LAN) systems. Achieving high sum capacity under proportional fairness constraints is a popular research topic. The sum capacity of multiuser OFDM is maximized when each subchannel is assigned to the user with the best channel-to-noise ratio for that subchannel, with power subsequently distributed by water-filling. Under proportional fairness constraints, the sum capacity is maximized in [14]. In this paper, we present two resource allocation algorithms in multiuser OFDM systems that achieve higher sum capacity with variable proportional fairness constraints than [14]. The proposed optimization problem considers maximizing the sum capacity while maintaining proportional fairness among users for each channel realization. However, good proportional fairness reduces the sum capacity. There is a tradeoff between sum capacity and fairness deviation. Hence, the proposed suboptimal algorithms are created to increase sum capacity without causing too much fairness deviation. In these suboptimal algorithms, subchannel and power allocation are carried out separately. We use a simple method to determine the total transmit power for each user. This method is easy to implement. Simulation results show that the proposed algorithms achieve higher sum capacity than [14] and keep almost the same proportional fairness among users when data rate requirements are large enough. We show that fairness efficiency of our proposed algorithms is over three times better than [11] while maintaining almost the same proportional fairness among users for high date rate requirements. In addition, we also propose an algorithm which releases fairness deviation among users in order to achieve high capacity.

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Yen, Pei Ru, and 顏珮儒. "Short Sales Constraint, Price Discovery, Market Efficiency and Fairness-Taiwan Top50 Tracker Fund." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/69459538212700444514.

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碩士
國立政治大學
財務管理研究所
95
To some extent, almost all stock markets locate short-sell constraints on the short selling transactions process; however, they never do so to ETF thanks to its higher transparency and liquidity making it an easy supervised equity. Further, ETF could be considered as a good implication for the stock market simply owing to its exemption from short sell constraints that brings a strong demand and supply structure In other words, if the ETF price is not equal to its fund NAV (net asset value), investors could make profits by buying back or selling ETFs; in the long run, the price will reverse to its NAV and maintain on a reasonable level. As a result, we could infer that if the price could fully reflect investors’ diversified opinions, the market will be more efficient, and we could expect Taiwan stock market to forge ahead soon. Hence, the key issue lies in a healthy short selling mechanism. This paper tries to figure out whether short sell constraints on Taiwan stock market have significant influence on stock price and price efficiency. We use Taiwan50 index and TW50 ETF daily and intraday data from TEJ database, employee Event Study Method, select two dates as our event date which are “the listed date for TW50 ETF,” and “Taiwan 50 stocks exemption from short selling regulations,” and try to examine the difference before and after the date. Additionally, by summarizing and analyzing the trading frequency changes before or after the periods, we try to understand and estimate how the short sellers trading behavior would vary due to the implementation of regulation.

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Silva, Frederico João Sousa da. "As isenções de IMI e de IMT nos conjuntos de prédios classificados como monumentos nacionais, de interesse público e de interesse municipal : uma questão de (in)coerência." Master's thesis, 2017. http://hdl.handle.net/10400.14/23805.

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Para a prossecução do interesse público o Estado pode recorrer ao seu poder de autoridade para impor aos cidadãos a prática de um determinado comportamento ou a sua omissão. É do interesse público, e assume-se como tarefa fundamental do Estado Português, a proteção e valorização do património cultural português, património este que é constituído tanto pela língua portuguesa, como pelo Mosteiro dos Jerónimos, em Lisboa, ou ainda pela Cultura da Vinha na Ilha do Pico, nos Açores. Neste trabalho interessou-nos perceber, em primeiro lugar, que tipos de instrumentos é que o legislador utilizou para promover, designadamente, juntos dos particulares a proteção e a valorização do património cultural português. As restrições administrativas de utilidade pública assumiram, assim, um papel de destaque neste trabalho. Este conhecimento prévio dos instrumentos administrativos que tutelam a proteção do património cultural é meramente instrumental, no entanto, afigurou-se-nos como fundamental para a perceção ampla e informada sobre a legalidade ou a constitucionalidade do tratamento fiscal dos bens que constituem o património cultural português. Neste contexto deu-se particular importância à análise do âmbito de aplicação das isenções de IMI e de IMT sobre os prédios classificados como monumento, conjunto e sítio. O Direito Fiscal, no âmbito do Direito do Património Cultural, assume uma função de promoção da proteção e valorização do património, fundamentalmente, através do desagravamento da tributação sobre esse património. Assim, o objetivo último deste trabalho foi perceber o modo de aplicação desse desagravamento fiscal e, essencialmente, se é aplicado de uma forma justa, igualitária e proporcional.
In order to pursue the public interest the State may use its power of authority to impose on its citizens a particular behaviour or its omission. The protection and enhancement of the Portuguese cultural heritage, which is constituted at the same time by the Portuguese language, Jerónimos Monastery in Lisbon and the viniculture on Ilha do Pico, is a matter of public interest and therefor arises as one of the Portuguese State’s fundamental tasks. In this endeavour, our focus was to identify and to understand what kind of legal instruments did the legislator use to protect and enhance the Portuguese Cultural heritage with private individuals. Public administrative constraints will thus play a prominent role in this work. Though the prior awareness of these public administrative legal measures is merely instrumental it proved to be fundamental to gain a broader and better informed perception about the legality and the constitutionality of the tax treatment that is given to the Portuguese cultural heritage. In this context it was given particular emphasis to the analysis of the scope of tax exemptions in place from the municipal property tax and the municipal property transfer tax on buildings listed as monuments, groups of buildings and sites. Through the establishment of tax relief measures and within the scope of Cultural Heritage Law, Tax Law plays its role on enhancing and protecting cultural heritage. Thus, the ultimate objective of this endeavour is to understand how these tax relief measures are applied and, essentially, assess if they are equally, fairly, and proportionally applied.

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Du, Plessis Hanri Magdalena. "The harmonisation of good faith and ubuntu in the South African common law of contract." Thesis, 2017. http://hdl.handle.net/10500/23606.

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The legal historical development of fairness in the South African common law of contract is investigated in the context of the political, social and economic developments of the last four centuries. It emerges that the common law of contract is still dominated by the ideologies of individualism and economic liberalism which were imported from English law during the nineteenth century. Together with the theories of legal positivism and formalism which are closely related to parliamentary sovereignty and the classical rule of law, these ideals were transposed into the common law of contract through the classical model of contract law which emphasises freedom and sanctity of contract and promotes legal certainty. This approach resulted in the negation of the court’s equitable discretion and the limitation of good faith which sustain the social and economic inequalities that were created under colonialism and exacerbated under apartheid rule. In stark contrast, the modern human rights culture grounded in human dignity and aimed at the promotion of substantive equality led to the introduction of modern contract theory in other parts of the world. The introduction of the Constitution as grounded in human dignity and aimed at the achievement of substantive equality has resulted in a sophisticated jurisprudence on human dignity that reflects a harmonisation between its Western conception as based on Kantian dignity and ubuntu which provides an African understanding thereof. In this respect, ubuntu plays an important role in infusing the common law of contract with African values and in promoting substantive equality between contracting parties in line with modern contract theory. It is submitted that this approach to human dignity should result in the development of good faith into a substantive rule of the common law of contract which can be used to set aside an unfair contract term or the unfair enforcement thereof.
Private Law
LL. D.

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Nikjah, Reza. "Performance evaluation and protocol design of fixed-rate and rateless coded relaying networks." Phd thesis, 2010. http://hdl.handle.net/10048/1674.

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The importance of cooperative relaying communication in substituting for, or complementing, multiantenna systems is described, and a brief literature review is presented. Amplify-and-forward (AF) and decode-and-forward (DF) relaying are investigated and compared for a dual-hop relay channel. The optimal strategy, source and relay optimal power allocation, and maximum cooperative gain are determined for the relay channel. It is shown that while DF relaying is preferable to AF relaying for strong source-relay links, AF relaying leads to more gain for strong source-destination or relay-destination links. Superimposed and selection AF relaying are investigated for multirelay, dual-hop relaying. Selection AF relaying is shown to be globally strictly outage suboptimal. A necessary condition for the selection AF outage optimality, and an upper bound on the probability of this optimality are obtained. A near-optimal power allocation scheme is derived for superimposed AF relaying. The maximum instantaneous rates, outage probabilities, and average capacities of multirelay, dual-hop relaying schemes are obtained for superimposed, selection, and orthogonal DF relaying, each with parallel channel cooperation (PCC) or repetition-based cooperation (RC). It is observed that the PCC over RC gain can be as much as 4 dB for the outage probabilities and 8.5 dB for the average capacities. Increasing the number of relays deteriorates the capacity performance of orthogonal relaying, but improves the performances of the other schemes. The application of rateless codes to DF relaying networks is studied by investigating three single-relay protocols, one of which is new, and three novel, low complexity multirelay protocols for dual-hop networks. The maximum rate and minimum energy per bit and per symbol are derived for the single-relay protocols under a peak power and an average power constraint. The long-term average rate and energy per bit, and relay-to-source usage ratio (RSUR), a new performance measure, are evaluated for the single-relay and multirelay protocols. The new single-relay protocol is the most energy efficient single-relay scheme in most cases. All the multirelay protocols exhibit near-optimal rate performances, but are vastly different in the RSUR. Several future research directions for fixed-rate and rateless coded cooperative systems, and frameworks for comparing these systems, are suggested.
Communications

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Книги з теми "Fairness constraints"

Chandramouli, Shyam Sundar. Network Resource Allocation Under Fairness Constraints. [New York, N.Y.?]: [publisher not identified], 2014.

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Alex, Whiting. Part V Fairness and Expeditiousness of ICC Proceedings, 40 Disclosure Challenges at the ICC. Oxford University Press, 2015. http://dx.doi.org/10.1093/law/9780198705161.003.0040.

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This Chapter provides a prosecutorial perspective on evidence and disclosure. It proceeds in two parts: the first part sketches out the disclosure regime at the ICC; the second part identifies the challenges that the prosecution faces in managing disclosure. The contribution examines the approaches adopted by Pre-Trial and Trial Chambers and their impact on prosecutorial strategy and practice. It deals with constraints on disclosure (e.g. provider confidentiality, and witness protection) and puts the difficulties encountered in the first cases (e.g. Lubanga) into perspective. Finally, it reflects on key aspects of the emerging evidentiary regime, such as the role of documentary evidence, witness examination and testimony, and judicial questioning. The contribution argues that disclosure is not a topic that will ‘go away’ or be solved, but will instead be a recurring issue at the tribunals, in particular, in cases involving large amounts of material.

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Tadros, Victor. To Do, To Die, To Reason Why. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198831549.001.0001.

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To Do, To Die, To Reason Why is concerned with a wide range of issues about the ethics of war and the legal regulation of war. It is especially concerned with the conduct of individuals, including whether they are required to follow orders to go to war, what moral constraints there are on killing in war, what makes people liable to be killed in war, and the extent to which the laws of war ought to reflect the morality of war. It defends a largely anti-authority view about the morality of war, and defends familiar moral constraints on killing in war, such as the Doctrine of Doing and Allowing and a version of the Doctrine of Double Effect. However, it argues that a much wider range of people are liable to be harmed or killed in war than is normally thought to be the case, on grounds of both causal involvement and fairness, and it argues that the laws of war should converge much more closely with the morality of war than is currently the case.

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Retallack, James. The Struggle Against Revolution. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199668786.003.0005.

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This chapter focuses on the repression unleashed against Social Democrats in Saxony and Germany under Bismarck’s Anti-Socialist Law (1878–90). The chapter’s perspective moves between the national, regional, and local levels to assess the range of options open to those who sought to eradicate the “threat” of Social Democracy. The first section examines the national context of Bismarck’s war on socialism, while the following section considers Saxon peculiarities (opportunities and constraints). The focus falls on plans to impose the Lesser State of Siege on Leipzig. The next section discusses the Social Democrats’ continuing success in Landtag and Reichstag elections and zooms in on election battles “in the trenches.” Two final sections consider groups and individuals who played other roles in suppressing Social Democracy, in monitoring the fairness of elections, and in trying to rewrite the “rules of the game” for future election contests.

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Karim A A, Khan QC, and Buisman Caroline. Part V Fairness and Expeditiousness of ICC Proceedings, 41 Sitting on Evidence?: Systemic Failings in the ICC Disclosure Regime—Time for Reform. Oxford University Press, 2015. http://dx.doi.org/10.1093/law/9780198705161.003.0041.

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The right to full and timely disclosure is one of the most fundamental rights of suspects and accused persons before the ICC. Regrettably, it is also the most violated right. This Chapter examines the difficulties the defence has encountered as a result of late, inadequate, or non-disclosure of material relevant to the case. Drawing heavily on the authors’ own experiences before the ICC, this contribution argues that the current disclosure regime of the ICC places an inordinate burden on limited defence resources, and improperly and unnecessarily constrains the ability of defence teams to effectively and efficiently prepare for and conduct the defence of the client. The Chapter makes a number of proposals for improvement, including management of time limits for final prosecution pre-trial disclosure, protective measures, transparency, and internal prosecution review.

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Bartley, Tim. Rules without Rights. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198794332.001.0001.

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Activists have exposed startling forms of labor exploitation and environmental degradation in global industries, leading many large retailers and brands to adopt standards for fairness and sustainability. This book is about the idea that transnational corporations can push these rules through their global supply chains, and in effect, pull factories, forests, and farms out of their local contexts and up to global best practices. For many scholars and practitioners, this kind of private regulation and global standard-setting can provide an alternative to regulation by territorially bound, gridlocked, or incapacitated nation states, potentially improving environments and working conditions around the world and protecting the rights of exploited workers, impoverished farmers, and marginalized communities. But can private, voluntary rules actually create meaningful forms of regulation? Are forests and factories around the world being made into sustainable ecosystems and decent workplaces? Can global norms remake local orders? This book provides striking new answers by comparing the private regulation of land and labor in democratic and authoritarian settings. Case studies of sustainable forestry and fair labor standards in Indonesia and China show not only how transnational standards are implemented “on the ground” but also how they are constrained and reconfigured by domestic governance. Combining rich multi-method analyses, a powerful comparative approach, and a new theory of private regulation, this book reveals the contours and contradictions of transnational governance.

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Частини книг з теми "Fairness constraints"

Baier, Christel, Marcus Groesser, and Frank Ciesinski. "Quantitative Analysis under Fairness Constraints." In Automated Technology for Verification and Analysis, 135–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04761-9_12.

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Allen Emerson, E., and Chin-Laung Lei. "Temporal reasoning under generalized fairness constraints." In STACS 86, 21–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/3-540-16078-7_62.

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Gullo, Francesco, Lucio La Cava, Domenico Mandaglio, and Andrea Tagarelli. "When Correlation Clustering Meets Fairness Constraints." In Discovery Science, 302–17. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-18840-4_22.

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Puhakka, Antti. "Using Fairness Constraints in Process-Algebraic Verification." In Theoretical Aspects of Computing – ICTAC 2005, 546–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11560647_36.

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Dorleon, Ginel, Imen Megdiche, Nathalie Bricon-Souf, and Olivier Teste. "Feature Selection Under Fairness and Performance Constraints." In Big Data Analytics and Knowledge Discovery, 125–30. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12670-3_11.

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Joung, Yuh-Jzer. "Localizability of Fairness Constraints and their Distributed Implementations." In CONCUR’99 Concurrency Theory, 336–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48320-9_24.

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Xu, Ziqi, Jixue Liu, Debo Cheng, Jiuyong Li, Lin Liu, and Ke Wang. "Disentangled Representation with Causal Constraints for Counterfactual Fairness." In Advances in Knowledge Discovery and Data Mining, 471–82. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-33374-3_37.

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Wang, Jingbo, Yannan Li, and Chao Wang. "Synthesizing Fair Decision Trees via Iterative Constraint Solving." In Computer Aided Verification, 364–85. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13188-2_18.

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AbstractDecision trees are increasingly used to make socially sensitive decisions, where they are expected to be both accurate and fair, but it remains a challenging task to optimize the learning algorithm for fairness in a predictable and explainable fashion. To overcome the challenge, we propose an iterative framework for choosing decision attributes, or features, at each level by formulating feature selection as a series of mixed integer optimization problems. Both fairness and accuracy requirements are encoded as numerical constraints and solved by an off-the-shelf constraint solver. As a result, the trade-off between fairness and accuracy is quantifiable. At a high level, our method can be viewed as a generalization of the entropy-based greedy search techniques such as and , and existing fair learning techniques such as and . Our experimental evaluation on six datasets, for which demographic parity is used as the fairness metric, shows that the method is significantly more effective in reducing bias than other methods while maintaining accuracy. Furthermore, compared to non-iterative constraint solving, our iterative approach is at least 10 times faster.

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Paraschakis, Dimitris, and Bengt J. Nilsson. "Matchmaking Under Fairness Constraints: A Speed Dating Case Study." In Communications in Computer and Information Science, 43–57. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52485-2_5.

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Krasanakis, Emmanouil, Symeon Papadopoulos, and Ioannis Kompatsiaris. "Applying Fairness Constraints on Graph Node Ranks Under Personalization Bias." In Complex Networks & Their Applications IX, 610–22. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65351-4_49.

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Тези доповідей конференцій з теми "Fairness constraints"

Padala, Manisha, and Sujit Gujar. "FNNC: Achieving Fairness through Neural Networks." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/315.

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In classification models, fairness can be ensured by solving a constrained optimization problem. We focus on fairness constraints like Disparate Impact, Demographic Parity, and Equalized Odds, which are non-decomposable and non-convex. Researchers define convex surrogates of the constraints and then apply convex optimization frameworks to obtain fair classifiers. Surrogates serve as an upper bound to the actual constraints, and convexifying fairness constraints is challenging. We propose a neural network-based framework, \emph{FNNC}, to achieve fairness while maintaining high accuracy in classification. The above fairness constraints are included in the loss using Lagrangian multipliers. We prove bounds on generalization errors for the constrained losses which asymptotically go to zero. The network is optimized using two-step mini-batch stochastic gradient descent. Our experiments show that FNNC performs as good as the state of the art, if not better. The experimental evidence supplements our theoretical guarantees. In summary, we have an automated solution to achieve fairness in classification, which is easily extendable to many fairness constraints.

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Celis, L. Elisa, Lingxiao Huang, Vijay Keswani, and Nisheeth K. Vishnoi. "Classification with Fairness Constraints." In FAT* '19: Conference on Fairness, Accountability, and Transparency. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3287560.3287586.

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Celis, L. Elisa, Lingxiao Huang, and Nisheeth K. Vishnoi. "Multiwinner Voting with Fairness Constraints." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/20.

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Multiwinner voting rules are used to select a small representative subset of candidates or items from a larger set given the preferences of voters. However, if candidates have sensitive attributes such as gender or ethnicity (when selecting a committee), or specified types such as political leaning (when selecting a subset of news items), an algorithm that chooses a subset by optimizing a multiwinner voting rule may be unbalanced in its selection -- it may under or over represent a particular gender or political orientation in the examples above. We introduce an algorithmic framework for multiwinner voting problems when there is an additional requirement that the selected subset should be ``fair'' with respect to a given set of attributes. Our framework provides the flexibility to (1) specify fairness with respect to multiple, non-disjoint attributes (e.g., ethnicity and gender) and (2) specify a score function. We study the computational complexity of this constrained multiwinner voting problem for monotone and submodular score functions and present several approximation algorithms and matching hardness of approximation results for various attribute group structure and types of score functions. We also present simulations that suggest that adding fairness constraints may not affect the scores significantly when compared to the unconstrained case.

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Cohen, Maxime C., Adam N. Elmachtoub, and Xiao Lei. "Price Discrimination with Fairness Constraints." In FAccT '21: 2021 ACM Conference on Fairness, Accountability, and Transparency. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3442188.3445864.

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Dorleon, Ginel, Imen Megdiche, Nathalie Bricon-Souf, and Olivier Teste. "Feature selection under fairness constraints." In SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3477314.3507168.

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Xu, Huanle, Yang Liu, Wing Cheong Lau, and Rui Li. "Combinatorial Multi-Armed Bandits with Concave Rewards and Fairness Constraints." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/354.

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The problem of multi-armed bandit (MAB) with fairness constraint has emerged as an important research topic recently. For such problems, one common objective is to maximize the total rewards within a fixed round of pulls, while satisfying the fairness requirement of a minimum selection fraction for each individual arm in the long run. Previous works have made substantial advancements in designing efficient online selection solutions, however, they fail to achieve a sublinear regret bound when incorporating such fairness constraints. In this paper, we study a combinatorial MAB problem with concave objective and fairness constraints. In particular, we adopt a new approach that combines online convex optimization with bandit methods to design selection algorithms. Our algorithm is computationally efficient, and more importantly, manages to achieve a sublinear regret bound with probability guarantees. Finally, we evaluate the performance of our algorithm via extensive simulations and demonstrate that it outperforms the baselines substantially.

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Kobren, Ari, Barna Saha, and Andrew McCallum. "Paper Matching with Local Fairness Constraints." In KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3292500.3330899.

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Li, Fengjiao, Jia Liu, and Bo Ji. "Combinatorial Sleeping Bandits with Fairness Constraints." In IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. IEEE, 2019. http://dx.doi.org/10.1109/infocom.2019.8737461.

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Xu, Weiting, Jie Hu, Shengdong Du, and Yan Yang. "K-Means Clustering with Fairness Constraints." In 2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE). IEEE, 2021. http://dx.doi.org/10.1109/iske54062.2021.9755376.

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Zeng, Yuchen, Hongxu Chen, and Kangwook Lee. "Federated Learning with Local Fairness Constraints." In 2023 IEEE International Symposium on Information Theory (ISIT). IEEE, 2023. http://dx.doi.org/10.1109/isit54713.2023.10206590.

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