An open-economy macro-finance model of international interdependence : The OECD, US and the UK

This paper develops a multi-country macro-finance model to study international economic and financial linkages. This approach models the economy and financial markets jointly using both types of data to throw light on such issues. The world economy is modelled using data for the US and aggregate OECD economies as well as the US Treasury bond market using latent variables to represent a common inflation trend and a US real interest rate factor. We find strong evidence of global effects on both the US and UK, calling into question the standard closed economy macro-finance specification. These economic linkages also help to explain the co-movement of yields in the US and UK Treasury bond markets. (C) 2009 Elsevier B.V. All rights reserved

Articulated Pose Estimation Using Hierarchical Exemplar-Based Models

Exemplar-based models have achieved great success on localizing the parts of semi-rigid objects. However, their efficacy on highly articulated objects such as humans is yet to be explored. Inspired by hierarchical object representation and recent application of Deep Convolutional Neural Networks (DCNNs) on human pose estimation, we propose a novel formulation that incorporates both hierarchical exemplar-based models and DCNNs in the spatial terms. Specifically, we obtain more expressive spatial models by assuming independence between exemplars at different levels in the hierarchy; we also obtain stronger spatial constraints by inferring the spatial relations between parts at the same level. As our method strikes a good balance between expressiveness and strength of spatial models, it is both effective and generalizable, achieving state-of-the-art results on different benchmarks: Leeds Sports Dataset and CUB-200-2011.Comment: 8 pages, 6 figure