نتایج جستجو برای: pooling data

تعداد نتایج: 2415372  

2009
Orazio Attanasio Abigail Barr Juan Camilo Cardenas Garance Genicot Costas Meghir

Using data from a field experiment conducted in seventy Colombian municipalities, we investigate who pools risk with whom when risk pooling arrangements are not formally enforced. We explore the roles played by risk attitudes and network connections both theoretically and empirically. We find that pairs of participants who share a bond of friendship or kinship are more likely to (1) join the sa...

2013
Franz Dietrich

We consider the classical problem of aggregating di¤erent individuals’probability assignments (opinions) over a -algebra of events. In practice, some events represent basic propositions, such as ‘it rains’or ‘CO2 emissions cause global warming’, while others represent combinations thereof, for instance disjunctions (unions) of basic events. It is plausible to treat the basic events as premises ...

حسین درگاهی, , سیدمنصور رضوی, ,

Background: This research have presented focuses upon the cultural side of managerial coordination and control as manifested in Telemedicine Technology. Specifically, the research seeks to analyze and determines the attitude of clinical physicians about the role of specific dimensions of organizational culture and organizational structure may have upon effective managerial coordination and cont...

2013
Mateusz Malinowski Mario Fritz

From the early HMAX model to Spatial Pyramid Matching, spatial pooling has played an important role in visual recognition pipelines. By aggregating local statistics, it equips the recognition pipelines with a certain degree of robustness to translation and deformation yet preserving spatial information. Despite of its predominance in current recognition systems, we have seen little progress to ...

Journal: :CoRR 2014
Orhan Firat Emre Aksan Ilke Oztekin Fatos T. Yarman Vural

Functional magnetic resonance imaging produces high dimensional data, with a less then ideal number of labelled samples for brain decoding tasks (predicting brain states). In this study, we propose a new deep temporal convolutional neural network architecture with spatial pooling for brain decoding which aims to reduce dimensionality of feature space along with improved classification performan...

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