2,147 research outputs found

    Runtime Optimizations for Prediction with Tree-Based Models

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    Tree-based models have proven to be an effective solution for web ranking as well as other problems in diverse domains. This paper focuses on optimizing the runtime performance of applying such models to make predictions, given an already-trained model. Although exceedingly simple conceptually, most implementations of tree-based models do not efficiently utilize modern superscalar processor architectures. By laying out data structures in memory in a more cache-conscious fashion, removing branches from the execution flow using a technique called predication, and micro-batching predictions using a technique called vectorization, we are able to better exploit modern processor architectures and significantly improve the speed of tree-based models over hard-coded if-else blocks. Our work contributes to the exploration of architecture-conscious runtime implementations of machine learning algorithms

    A Context-Aware Mobile Recommender System for Places of Interest

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    In this paper we introduce a novel setting mindful portable recommender framework for spots of intrigue (POIs). Not at all like existing frameworks, which gain clients' inclinations exclusively from their past evaluations, has it considered additionally their identity - utilizing the Five Factor Model. Identity is gained by requesting that clients finish a brief and engaging poll as a major aspect of the enlistment procedure, and is then misused in: (1) a dynamic learning module that effectively obtains evaluations in-setting for POIs that clients are probably going to have encountered, consequently diminishing the anxiety and inconvenience to rate (or skip rating) things that the clients don't have a clue; and (2) in the suggestion display that develops on network factorization and in this manner can be prepared regardless of the possibility that the clients haven't appraised any things yet

    How Production Firms Adapt to War: e Case of Liberia

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    How do production firms adapt to civil war? The answer to this question will inform the potential for economic development during and after conflict. Many businesses survive violent conflict, and in some cases even thrive. Understanding these successes will help policymakers to support the “coping economy” during civil wars, and to understand better the post-conflict economy as a system. In this paper I use the case of production firms operating in Liberia’s capital, Monrovia, during the country’s civil war to argue that successful wartime firms continually adapt their supply chain structures in response to a shifting combat frontier by dispersing their functions spatially and temporally. Such adaptability depends on the rapid gathering (via business networks) and processing (at the place of production) of information. This contention represents a micro-level explanation for, and also a conditioning of, the generally accepted view that industries that survive civil war tend to be non-capital intensive and non-trade intensive.production firms, civil war, conflict economics, post-conflict recovery, economic resiliency, Liberia

    Evaluating Future Nanotechnology: The Net Societal Impacts of Atomically Precise Manufacturing

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    Atomically precise manufacturing (APM) is the assembly of materials with atomic precision. APM does not currently exist, and may not be feasible, but if it is feasible, then the societal impacts could be dramatic. This paper assesses the net societal impacts of APM across the full range of important APM sectors: general material wealth, environmental issues, military affairs, surveillance, artificial intelligence, and space travel. Positive effects were found for material wealth, the environment, military affairs (specifically nuclear disarmament), and space travel. Negative effects were found for military affairs (specifically rogue actor violence and AI. The net effect for surveillance was ambiguous. The effects for the environment, military affairs, and AI appear to be the largest, with the environment perhaps being the largest of these, suggesting that APM would be net beneficial to society. However, these factors are not well quantified and no definitive conclusion can be made. One conclusion that can be reached is that if APM R&D is pursued, it should go hand-in-hand with effective governance strategies to increase the benefits and reduce the harms

    Safe Deployment for Counterfactual Learning to Rank with Exposure-Based Risk Minimization

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    Counterfactual learning to rank (CLTR) relies on exposure-based inverse propensity scoring (IPS), a LTR-specific adaptation of IPS to correct for position bias. While IPS can provide unbiased and consistent estimates, it often suffers from high variance. Especially when little click data is available, this variance can cause CLTR to learn sub-optimal ranking behavior. Consequently, existing CLTR methods bring significant risks with them, as naively deploying their models can result in very negative user experiences. We introduce a novel risk-aware CLTR method with theoretical guarantees for safe deployment. We apply a novel exposure-based concept of risk regularization to IPS estimation for LTR. Our risk regularization penalizes the mismatch between the ranking behavior of a learned model and a given safe model. Thereby, it ensures that learned ranking models stay close to a trusted model, when there is high uncertainty in IPS estimation, which greatly reduces the risks during deployment. Our experimental results demonstrate the efficacy of our proposed method, which is effective at avoiding initial periods of bad performance when little data is available, while also maintaining high performance at convergence. For the CLTR field, our novel exposure-based risk minimization method enables practitioners to adopt CLTR methods in a safer manner that mitigates many of the risks attached to previous methods.Comment: SIGIR 2023 - Full pape

    Developing Email Interview Practices in Qualitative Research

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    This article describes using email as a kind of interview. In a sociological study of professional career transition into law, on several occasions in that study, interview participants suggested using emails rather than face-to-face interviews. This \'irregularity\' set off reflection whether email interviews counted as \'proper\' interviews. Discussing examples of email interviews clarifies differences from other uses of email in research, and assists exploration of advantages and disadvantages of email interviews as a qualitative research method. A preliminary framework is suggested for evaluation the suitability of email interviews. Present-day limitations point to continuing development in this area of social research. Current indications are that emergent media technologies such as email interviews, like other new media innovations, do not diminish older forms, but rather enrich the array of investigatory tools available for social research today.Email Interview; Email Research; Interview Methodology; Mixed Method

    Everyday Life and Everyday Communication in Coronavirus Capitalism

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    In 2020, the coronavirus crisis ruptured societies and their everyday life around the globe. This article is a contribution to critically theorising the changes societies have undergone in the light of the coronavirus crisis. It asks: How have everyday life and everyday communication changed in the coronavirus crisis? How does capitalism shape everyday life and everyday communication during this crisis? Section 2 focuses on how social space, everyday life, and everyday communication have changed in the coronavirus crisis. Section 3 focuses on the communication of ideology in the context of coronavirus by analysing the communication of coronavirus conspiracy stories and false coronavirus news. The coronavirus crisis is an existential crisis of humanity and society. It radically confronts humans with death and the fear of death. This collective experience can on the one hand result in new forms of solidarity and socialism or can on the other hand, if ideology and the far-right prevail, advance war and fascism. Political action and political economy are decisive factors in such a profound crisis that shatters society and everyday life

    Aid and growth in small island developing states

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    Aid flows to small island developing states (SIDS) are enormous by international standards when compared to the size of their economies. Yet these countries face many severe economic challenges and many have experienced declines in the living standards of their citizens. This paper looks at the impact of aid on what is treated as a necessary precondition for improvements in living standards, typically defined. Specifically, it examines the impact of foreign aid on real per capita income growth in SIDS by econometrically analysing cross-country data for the period 1980 to 2004. A variety of econometric techniques and measures of aid are used. Results suggest that foreign aid is effective at spurring economic growth but with diminishing returns.<br /
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