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1.	Berggren, Björn, 1972-, et al. (author) The effect of business cycles on entrepreneurial control aversion and the search for external financing in SMEs 2009 In: International Journal of Business Strategy. - 1553-9563 .- 2378-8585. ; 9:2, s. 33-47 Conference paper (peer-reviewed)
2.	Boano, Carlo Alberto, et al. (author) Controllable radio interference for experimental and testing purposes in wireless sensor networks 2009. - 1 Conference paper (peer-reviewed)
3.	Cunningham, Gary, 1941-, et al. (author) Towards a Theory of Performance Reporting in Achieving Public Sector Accountability: A Field Study 2000 In: Towards a Theory of Performance Reporting in Achieving Public Sector Accountability: A Field Study. - Beijing, China. Conference paper (peer-reviewed)
4.	Hjalmarsson, Håkan, 1962-, et al. (author) Composite modeling of transfer functions 1995 In: Proceedings of the IEEE Conference on Decision and Control. - New Orleans, LA, USA : Institute of Electrical and Electronics Engineers (IEEE). - 0780326857 ; 40:5, s. 820-832 Conference paper (peer-reviewed)abstract The problem under consideration is how to estimate the frequency function of a system and the associated estimation error when a set of possible model structures is given and when one of them is known to contain the true system. The 'classical' solution to this problem is to, firstly, use a consistent model structure selection criterium to discard all but one single structure. Secondly, estimate a model in this structure and, thirdly, conditioned on the assumption that the chosen structure contains the true system, compute an estimate of the estimation error. However, for a finite data set one cannot guarantee that the correct structure is chosen and this 'structural' uncertainty is lost in the previously mentioned approach. In this contribution a method is developed that combines the frequency function estimates and the estimation errors from all possible structures into a joint estimate and estimation error. Hence, this approach by-passes the structure selection problem. This is accomplished by employing a Bayesian setting.
5.	Löfström, Tuve, et al. (author) Ensemble member selection using multi-objective optimization 2009 In: IEEE Symposium on Computational Intelligence and Data Mining. - : IEEE conference proceedings. - 9781424427659 ; , s. 245-251 Conference paper (peer-reviewed)abstract Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ensemble accuracy is, especially for classification, far from solved. In essence, the key problem is to find a suitable criterion, typically based on training or selection set performance, highly correlated with ensemble accuracy on novel data. Several studies have, however, shown that it is difficult to come up with a single measure, such as ensemble or base classifier selection set accuracy, or some measure based on diversity, that is a good general predictor for ensemble test accuracy. This paper presents a novel technique that for each learning task searches for the most effective combination of given atomic measures, by means of a genetic algorithm. Ensembles built from either neural networks or random forests were empirically evaluated on 30 UCI datasets. The experimental results show that when using the generated combined optimization criteria to rank candidate ensembles, a higher test set accuracy for the top ranked ensemble was achieved, compared to using ensemble accuracy on selection data alone. Furthermore, when creating ensembles from a pool of neural networks, the use of the generated combined criteria was shown to generally outperform the use of estimated ensemble accuracy as the single optimization criterion.
6.	Löfström, Tuve, et al. (author) On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers 2008 In: 2008 Seventh International Conference on Machine Learning and Applications. - : IEEE. - 9780769534954 ; , s. 127-132 Conference paper (peer-reviewed)abstract The test set accuracy for ensembles of classifiers selected based on single measures of accuracy and diversity as well as combinations of such measures is investigated. It is found that by combining measures, a higher test set accuracy may be obtained than by using any single accuracy or diversity measure. It is further investigated whether a multi-criteria search for an ensemble that maximizes both accuracy and diversity leads to more accurate ensembles than by optimizing a single criterion. The results indicate that it might be more beneficial to search for ensembles that are both accurate and diverse. Furthermore, the results show that diversity measures could compete with accuracy measures as selection criterion.
7.	Nordvall, Anna-Carin, 1976-, et al. (author) Non-linear Multiple Cue Judgment tasks 2005 Conference paper (peer-reviewed)
8.	Svahn, Fredrik, 1972 (author) The Sociomateriality of Competing Technological Regimes in Digital Innovation 2009 In: Proceedings of the 32nd Information Systems Research Seminar in Scandinavia. - Molde, Norway : Tapir Academic Press. ; , s. 23-40 Conference paper (peer-reviewed)
9.	Nilsson, Magnus (author) Pensioner and "elderly" as political identities 2005 In: 5th International Symposium on Cultural Gerontology: Current and Future Pasts, The Open University, Milton Keynes, UK, 19-21 maj 2005. Conference paper (peer-reviewed)
10.	Kristiansson, Erik, 1978, et al. (author) Characterization of the Zoarces viviparus liver transcriptome using massively parallel pyrosequencing 2009 In: SETAC Europe 19th Annual Meeting Abstract Book, Göteborg 31 May - 4 June, 2009. Conference paper (peer-reviewed)

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Type of publication: conference paper (60685); artistic work (7)

Type of content: peer-reviewed (60685)

Author/Editor: Kildal, Per-Simon, 1 ... (286); Laurell, Fredrik (234); Claesson, Ingvar (206); Zaslavsky, Arkady (196); Iwarsson, Susanne (171); Pasiskevicius, Valda ... (165); show more...; Turner, Anthony, 195 ... (164); Tenhunen, Hannu (158); Jantsch, Axel (156); Liu, Johan, 1960 (154); Samuelson, Lars (144); Sundén, Bengt (137); Johansson, Karl Henr ... (128); Janzén, Erik (127); Johansson, Rolf (123); Lennartson, Bengt, 1 ... (122); Fuchs, Laszlo (119); Ottersten, Björn, 19 ... (118); Gustafsson, Fredrik (118); Söder, Lennart (116); Skoglundh, Magnus, 1 ... (115); Svensson, Arne, 1955 (111); Fransson, Torsten (110); Kaplan, Alexander (102); Fritzson, Peter (102); Mohammed, Abbas (99); Peng, Zebo, 1958- (97); Ljung, Lennart, 1946 ... (96); Johansson, Bengt (95); Blomgren, J (94); Larsson, Andreas (94); Molisch, Andreas (90); Nilsson, Peter (89); Stemme, Göran (88); Borrebaeck, Carl (87); Leckner, Bo G, 1936 (87); Robertsson, Anders (86); Wang, Lihui (86); Davidsson, Paul (85); Johansson, Mikael (85); Hjalmarsson, Håkan, ... (83); Zheng, Li-Rong (83); Sundqvist, Bertil (83); Skoglund, Mikael (83); Voigt, Thiemo (81); Zirath, Herbert, 195 ... (79); Janzén, Erik, 1954- (77); Gustafsson, Mats (77); Saffiotti, Alessandr ... (77); Eles, Petru Ion, 195 ... (77); show less...

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