| 1. |
- Acs, Zoltan J., et al.
(författare)
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Philippe Aghion : recipient of the 2016 Global Award for Entrepreneurship Research
- 2017
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Ingår i: Small Business Economics. - : Springer. - 0921-898X .- 1573-0913. ; 48:1, s. 1-8
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Tidskriftsartikel (refereegranskat)abstract
- Professor Philippe Aghion is the 2016 recipient of the Global Award for Entrepreneurship Research, consisting of 100,000 Euros and a statuette designed by the internationally renowned Swedish sculptor Carl Milles. He is one of the most influential researchers worldwide in economics in the last couple of decades. His research has advanced our understanding of the relationship between firm-level innovation, entry and exit on the one hand, and productivity and growth on the other. Aghion has thus accomplished to bridge theoretical macroeconomic growth models with a more complete and consistent microeconomic setting. He is one of the founding fathers of the pioneering and original contribution referred to as Schumpeterian growth theory. Philippe Aghion has not only contributed with more sophisticated theoretical models, but also provided empirical evidence regarding the importance of entrepreneurial endeavours for societal prosperity, thereby initiating a more nuanced policy discussion concerning the interdependencies between entrepreneurship, competition, wealth and growth.
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| 2. |
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| 3. |
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Agglomeration, clusters and entrepreneurship : Studies in regional economic development
- 2014
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- Regional economic development has experienced considerable dynamism over recent years. Perhaps the most notable cases were the rise of China and India to emergent country status by the turn of the millennium. With time now for hindsight, this book identifies some of the key forces behind these development successes, namely agglomeration, clusters and entrepreneurship.
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| 4. |
- Ahlberg, Ernst, et al.
(författare)
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Using conformal prediction to prioritize compound synthesis in drug discovery
- 2017
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Ingår i: Proceedings of Machine Learning Research. - Stockholm : Machine Learning Research. ; , s. 174-184
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Konferensbidrag (refereegranskat)abstract
- The choice of how much money and resources to spend to understand certain problems is of high interest in many areas. This work illustrates how computational models can be more tightly coupled with experiments to generate decision data at lower cost without reducing the quality of the decision. Several different strategies are explored to illustrate the trade off between lowering costs and quality in decisions.AUC is used as a performance metric and the number of objects that can be learnt from is constrained. Some of the strategies described reach AUC values over 0.9 and outperforms strategies that are more random. The strategies that use conformal predictor p-values show varying results, although some are top performing.The application studied is taken from the drug discovery process. In the early stages of this process compounds, that potentially could become marketed drugs, are being routinely tested in experimental assays to understand the distribution and interactions in humans.
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| 5. |
- Ahlgren, Per, 1960-, et al.
(författare)
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Document-document similarity approaches and science mapping: experimental comparison of five approaches
- 2009
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Ingår i: Journal of Informetrics. - Netherlands : Elsevier BV. - 1751-1577 .- 1875-5879. ; 3:1, s. 49-63
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Tidskriftsartikel (refereegranskat)abstract
- This paper treats document–document similarity approaches in the context of science mapping. Five approaches, involving nine methods, are compared experimentally. We compare text-based approaches, the citation-based bibliographic coupling approach, and approaches that combine text-based approaches and bibliographic coupling. Forty-three articles, published in the journal Information Retrieval, are used as test documents. We investigate how well the approaches agree with a ground truth subject classification of the test documents, when the complete linkage method is used, and under two types of similarities, first-order and second-order. The results show that it is possible to achieve a very good approximation of the classification by means of automatic grouping of articles. One text-only method and one combination method, under second-order similarities in both cases, give rise to cluster solutions that to a large extent agree with the classification.
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| 6. |
- Alkhatib, Amr, et al.
(författare)
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Approximating Score-based Explanation Techniques Using Conformal Regression
- 2023
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Ingår i: Proceedings of Machine Learning Research. - : ML Research Press. ; , s. 450-469, s. 450-469
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Konferensbidrag (refereegranskat)abstract
- Score-based explainable machine-learning techniques are often used to understand the logic behind black-box models. However, such explanation techniques are often computationally expensive, which limits their application in time-critical contexts. Therefore, we propose and investigate the use of computationally less costly regression models for approximating the output of score-based explanation techniques, such as SHAP. Moreover, validity guarantees for the approximated values are provided by the employed inductive conformal prediction framework. We propose several non-conformity measures designed to take the difficulty of approximating the explanations into account while keeping the computational cost low. We present results from a large-scale empirical investigation, in which the approximate explanations generated by our proposed models are evaluated with respect to efficiency (interval size). The results indicate that the proposed method can significantly improve execution time compared to the fast version of SHAP, TreeSHAP. The results also suggest that the proposed method can produce tight intervals, while providing validity guarantees. Moreover, the proposed approach allows for comparing explanations of different approximation methods and selecting a method based on how informative (tight) are the predicted intervals.
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| 7. |
- Alkhatib, Amr, et al.
(författare)
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Assessing Explanation Quality by Venn Prediction
- 2022
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Ingår i: Proceedings of the 11th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2022. - : ML Research Press. ; , s. 42-54, s. 42-54
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Konferensbidrag (refereegranskat)abstract
- Rules output by explainable machine learning techniques naturally come with a degree of uncertainty, as the complex functionality of the underlying black-box model often can be difficult to approximate by a single, interpretable rule. However, the uncertainty of these approximations is not properly quantified by current explanatory techniques. The use of Venn prediction is here proposed and investigated as a means to quantify the uncertainty of the explanations and thereby also allow for competing explanation techniques to be evaluated with respect to their relative uncertainty. A number of metrics of rule explanation quality based on uncertainty are proposed and discussed, including metrics that capture the tendency of the explanations to predict the correct outcome of a black-box model on new instances, how informative (tight) the produced intervals are, and how certain a rule is when predicting one class. An empirical investigation is presented, in which explanations produced by the state-of-the-art technique Anchors are compared to explanatory rules obtained from association rule mining. The results suggest that the association rule mining approach may provide explanations with less uncertainty towards the correct label, as predicted by the black-box model, compared to Anchors. The results also show that the explanatory rules obtained through association rule mining result in tighter intervals and are closer to either one or zero compared to Anchors, i.e., they are more certain towards a specific class label.
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| 8. |
- Allwood, Jens, et al.
(författare)
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The MUMIN coding scheme for the annotation of feedback, turn management and sequencing phenomena
- 2007
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Ingår i: Language resources and evaluation. - : Springer Science and Business Media LLC. - 1574-020X .- 1574-0218 .- 1572-8412. ; 41:3-4, s. 273-287
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Tidskriftsartikel (refereegranskat)abstract
- This paper deals with a multimodal annotation scheme dedicated to the study of gestures in interpersonal communication, with particular regard to the role played by multimodal expressions for feedback, turn management and sequencing. The scheme has been developed under the framework of the MUMIN network and tested on the analysis of multimodal behaviour in short video clips in Swedish, Finnish and Danish. The preliminary results obtained in these studies show that the reliability of the categories defined in the scheme is acceptable, and that the scheme as a whole constitutes a versatile analysis tool for the study of multimodal communication behaviour.
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| 9. |
- Anderson, Helén, et al.
(författare)
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Skapa kundnärvaro i innovationsprocessen
- 2008
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Ingår i: Innovationsförmåga. - Malmö : Holmbergs i Malmö AB. - 9789197785204 ; , s. 40-59
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Bokkapitel (populärvet., debatt m.m.)
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| 10. |
- Andersson, David Emanuely, et al.
(författare)
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The geography of science in 12 European countries : a NUTS2-level analysis
- 2020
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Ingår i: Scientometrics. - : Springer Nature. - 0138-9130 .- 1588-2861. ; 124:2, s. 1099-1125
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Tidskriftsartikel (refereegranskat)abstract
- Europe has a long history as a global center of scientific research, but not all European regions are alike. Regions such as ile de France and the corridor that stretches from Cambridge to Oxford via London produce a disproportionate share of Europe's science output. An econometric analysis sheds light on the factors that explain the spatial distribution of European science. One result is that the regional volume of Web of Science publications depends on the regional number of researchers in higher education institutions. This is however not the only cause of high output. Universities and their surrounding regions are slowly evolving institutional structures. Some regions host universities that are more than 500 years old. A second key result is that an increase in the age of a region's oldest university is associated with greater output, other things being equal. Third, interregional accessibility via road, rail, and air networks is important for small regions, but not for large ones. Conversely, regional high-tech R&D employment is important for large but not for small regions.
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