7,429 research outputs found
On the Generation of Realistic and Robust Counterfactual Explanations for Algorithmic Recourse
This recent widespread deployment of machine learning algorithms presents many new challenges. Machine learning algorithms are usually opaque and can be particularly difficult to interpret. When humans are involved, algorithmic and automated decisions can negatively impact peopleâs lives. Therefore, end users would like to be insured against potential harm. One popular way to achieve this is to provide end users access to algorithmic recourse, which gives end users negatively affected by algorithmic decisions the opportunity to reverse unfavorable decisions, e.g., from a loan denial to a loan acceptance. In this thesis, we design recourse algorithms to meet various end user needs. First, we propose methods for the generation of realistic recourses. We use generative models to suggest recourses likely to occur under the data distribution. To this end, we shift the recourse action from the input space to the generative modelâs latent space, allowing to generate counterfactuals that lie in regions with data support. Second, we observe that small changes applied to the recourses prescribed to end users likely invalidate the suggested recourse after being nosily implemented in practice. Motivated by this observation, we design methods for the generation of robust recourses and for assessing the robustness of recourse algorithms to data deletion requests. Third, the lack of a commonly used code-base for counterfactual explanation and algorithmic recourse algorithms and the vast array of evaluation measures in literature make it difficult to compare the per formance of different algorithms. To solve this problem, we provide an open source benchmarking library that streamlines the evaluation process and can be used for benchmarking, rapidly developing new methods, and setting up new
experiments. In summary, our work contributes to a more reliable interaction of end users and machine learned models by covering fundamental aspects of the recourse process and suggests new solutions towards generating realistic and robust counterfactual explanations for algorithmic recourse
Search for long lived particles decaying into the semi leptonic di-tau final state with the ATLAS detector at the LHC
Many theoretical extensions of the Standard Model predict the existence of new long-lived particles that are within the discovery reach of the Large Hadron Collider (LHC).
This thesis presents a search for long-lived particles that decay to a pair of tau leptons, one then decaying hadronically and the other leptonically. Tau final states are on the interface between leptonic and hadronic searches and are much less thoroughly constrained.
Several approaches are taken to address some of the experimental challenges encountered in the search for displaced hadronic taus. The development of a novel tau track classification algorithm capable of accurately identifying tracks belonging to taus decaying to one or three charged pions is detailed. The resulting displaced track classifier demonstrates significantly higher efficiency compared to the nominal recommendations. Enhancements made to the existing ATLAS track classification algorithm in preparation for Run 3 data taking at the LHC are also outlined.
A newly developed RNN-based algorithm for identifying displaced tau leptons is presented in this thesis. When combined with the displaced track classification algorithm, this results in a displaced tau identification procedure that significantly improves background rejection and signal acceptance for displaced taus in a model-independent way. With efficiency gains of classifying 1-prong taus from about 40% to 80% and 3-prong taus from about 20% to 60%.
The thesis primarily presents a methodology combining reconstruction and identification techniques which are then folded into an analysis targeting exotic long-lived particles decaying to tau leptons. This signature-driven analysis targets the first stringent limits on long-lived particles decaying to third generation leptons. Major steps in this analysis have been taken and results presented
Configuration Management of Distributed Systems over Unreliable and Hostile Networks
Economic incentives of large criminal profits and the threat of legal consequences have pushed criminals to continuously improve their malware, especially command and control channels. This thesis applied concepts from successful malware command and control to explore the survivability and resilience of benign configuration management systems.
This work expands on existing stage models of malware life cycle to contribute a new model for identifying malware concepts applicable to benign configuration management. The Hidden Master architecture is a contribution to master-agent network communication. In the Hidden Master architecture, communication between master and agent is asynchronous and can operate trough intermediate nodes. This protects the master secret key, which gives full control of all computers participating in configuration management. Multiple improvements to idempotent configuration were proposed, including the definition of the minimal base resource dependency model, simplified resource revalidation and the use of imperative general purpose language for defining idempotent configuration.
Following the constructive research approach, the improvements to configuration management were designed into two prototypes. This allowed validation in laboratory testing, in two case studies and in expert interviews. In laboratory testing, the Hidden Master prototype was more resilient than leading configuration management tools in high load and low memory conditions, and against packet loss and corruption. Only the research prototype was adaptable to a network without stable topology due to the asynchronous nature of the Hidden Master architecture.
The main case study used the research prototype in a complex environment to deploy a multi-room, authenticated audiovisual system for a client of an organization deploying the configuration. The case studies indicated that imperative general purpose language can be used for idempotent configuration in real life, for defining new configurations in unexpected situations using the base resources, and abstracting those using standard language features; and that such a system seems easy to learn.
Potential business benefits were identified and evaluated using individual semistructured expert interviews. Respondents agreed that the models and the Hidden Master architecture could reduce costs and risks, improve developer productivity and allow faster time-to-market. Protection of master secret keys and the reduced need for incident response were seen as key drivers for improved security. Low-cost geographic scaling and leveraging file serving capabilities of commodity servers were seen to improve scaling and resiliency. Respondents identified jurisdictional legal limitations to encryption and requirements for cloud operator auditing as factors potentially limiting the full use of some concepts
Effective player guidance in logic puzzles
Pen & paper puzzle games are an extremely popular pastime, often enjoyed by demographics normally not considered to be âgamersâ. They are increasingly used as âserious gamesâ and there has been extensive research into computationally generating and efficiently solving them. However, there have been few academic studies that have focused on the players themselves. Presenting an appropriate level of challenge to a player is essential for both player enjoyment and engagement. Providing appropriate assistance is an essential mechanic for making a game accessible to a variety of players. In this thesis, we investigate how players solve Progressive Pen & Paper Puzzle Games (PPPPs) and how to provide meaningful assistance that allows players to recover from being stuck, while not reducing the challenge to trivial levels. This thesis begins with a qualitative in-person study of Sudoku solving. This study demonstrates that, in contrast to all existing assumptions used to model players, players were unsystematic, idiosyncratic and error-prone. We then designed an entirely new approach to providing assistance in PPPPs, which guides players towards easier deductions rather than, as current systems do, completing the next cell for them. We implemented a novel hint system using our design, with the assessment of the challenge being done using Minimal Unsatisfiable Sets (MUSs). We conducted four studies, using two different PPPPs, that evaluated the efficacy of the novel hint system compared to the current hint approach. The studies demonstrated that our novel hint system was as helpful as the existing system while also improving the player experience and feeling less like cheating. Players also chose to use our novel hint system significantly more often. We have provided a new approach to providing assistance to PPPP players and demonstrated that players prefer it over existing approaches
Multidisciplinary perspectives on Artificial Intelligence and the law
This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (âAIâ) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics â and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the CatĂłlica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
La traduzione specializzata allâopera per una piccola impresa in espansione: la mia esperienza di internazionalizzazione in cinese di Bioretics© S.r.l.
Global markets are currently immersed in two all-encompassing and unstoppable processes: internationalization and globalization. While the former pushes companies to look beyond the borders of their country of origin to forge relationships with foreign trading partners, the latter fosters the standardization in all countries, by reducing spatiotemporal distances and breaking down geographical, political, economic and socio-cultural barriers. In recent decades, another domain has appeared to propel these unifying drives: Artificial Intelligence, together with its high technologies aiming to implement human cognitive abilities in machinery. The âLanguage Toolkit â Le lingue straniere al servizio dellâinternazionalizzazione dellâimpresaâ project, promoted by the Department of Interpreting and Translation (ForlĂŹ Campus) in collaboration with the Romagna Chamber of Commerce (ForlĂŹ-Cesena and Rimini), seeks to help Italian SMEs make their way into the global market. It is precisely within this project that this dissertation has been conceived. Indeed, its purpose is to present the translation and localization project from English into Chinese of a series of texts produced by Bioretics© S.r.l.: an investor deck, the company website and part of the installation and use manual of the Aliquis© framework software, its flagship product. This dissertation is structured as follows: Chapter 1 presents the project and the company in detail; Chapter 2 outlines the internationalization and globalization processes and the Artificial Intelligence market both in Italy and in China; Chapter 3 provides the theoretical foundations for every aspect related to Specialized Translation, including website localization; Chapter 4 describes the resources and tools used to perform the translations; Chapter 5 proposes an analysis of the source texts; Chapter 6 is a commentary on translation strategies and choices
Provably safe systems: the only path to controllable AGI
We describe a path to humanity safely thriving with powerful Artificial
General Intelligences (AGIs) by building them to provably satisfy
human-specified requirements. We argue that this will soon be technically
feasible using advanced AI for formal verification and mechanistic
interpretability. We further argue that it is the only path which guarantees
safe controlled AGI. We end with a list of challenge problems whose solution
would contribute to this positive outcome and invite readers to join in this
work.Comment: 17 page
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