Factor Graph Based LMMSE Filtering for Colored Gaussian Processes

We propose a low complexity, graph based linear minimum mean square error (LMMSE) filter in which the non-white characteristics of a random process are taken into account. Our method corresponds to block LMMSE filtering, and has the advantage of complexity linearly increasing with the block length and the ease of incorporating the a priori information of the input signals whenever possible. The proposed method can be used with any random process with a known autocorrelation function with the help of an approximation to an autoregressive (AR) process. We show through extensive simulations that our method performs very close to the optimal block LMMSE filtering for Gaussian input signals.Comment: 5 pages, 4 figure

Structural change within the services sector, Baumol's cost disease, and cross-country productivity differences

I analyze structural change within the services sector and its implications for Baumol's cost disease and cross-country productivity differences. My results show that Baumol's cost disease becomes less relevant over development: It generates minor declines on aggregate productivity growth rate and accounts for a small share of the productivity growth slow- down. I argue that the existence of services sub-sectors with high-productivity growth rates, progressive services, and their substitutability with other sectors in the economy rationalize these facts. A model consistent with these stylized facts predict that Baumol's cost disease would depress aggregate productivity growth rate less in the future for developed countries. I later analyze cross-country productivity differences. The results in Duarte and Restuccia (2010) hide discrepancies between different services sub-sectors: Although developed countries have caught-up the US in the low-productivity growth services sub-sectors, stagnant services, the opposite conclusions emerge for the progressive/business services. I conclude that the substitutability between progressive/business and stagnant services sectors contribute to increasing aggregate productivity differences between the US and other developed countries. To put differently, structural change facts that limit Baumol's cost disease also advance cross-country productivity differences

Structural change within the services sector, Baumol's cost disease, and cross-country productivity differences

I analyze structural change within the services sector and its implications for Baumol's cost disease and cross-country productivity differences. My results show that Baumol's cost disease becomes less relevant over development: It generates minor declines on aggregate productivity growth rate and accounts for a small share of the productivity growth slow- down. I argue that the existence of services sub-sectors with high-productivity growth rates, progressive services, and their substitutability with other sectors in the economy rationalize these facts. A model consistent with these stylized facts predict that Baumol's cost disease would depress aggregate productivity growth rate less in the future for developed countries. I later analyze cross-country productivity differences. The results in Duarte and Restuccia (2010) hide discrepancies between different services sub-sectors: Although developed countries have caught-up the US in the low-productivity growth services sub-sectors, stagnant services, the opposite conclusions emerge for the progressive/business services. I conclude that the substitutability between progressive/business and stagnant services sectors contribute to increasing aggregate productivity differences between the US and other developed countries. To put differently, structural change facts that limit Baumol's cost disease also advance cross-country productivity differences

Essays on Productivity and Structural Change within the Services Sector

My PhD thesis consists of three chapters. The first chapter revisits the results in Bernard and Jones (1996) that argue that a group of 14 OECD countries does not converge in the manufacturing sector. For an updated dataset I show that the non-catch-up in the manufacturing sector result still prevails for the standard estimators, but when I allow for parametrical heterogeneity it is overturned. I conclude that the estimators allowing for parametrical heterogeneity, for example MG and CDMG, can deal with the cross-country level measurement issues inherent for the manufacturing sector and reverse the pathological results about the convergence. The second chapter focuses on the role of the services sector for aggregate productivity growth and cross-country productivity differences. I show that, because of the substitutability between high- and low-productivity growth services sectors (progressive and stagnant services sectors), structural change would not take down aggregate productivity growth further in the future for developed countries. My results also reveal that this substitutability within the services sector contributes to productivity differences between the US and other developed countries. In the third chapter of my PhD thesis I want to understand the deeper causes behind the substitutability between progressive and stagnant services sectors. My results reveal that the substitutability of the progressive services with other sectors in the economy remains robust to the changes in input/output table and structural change within the investment value added. I note that the positive correlation between the nominal and real value added shares reflects the presence of progressive services. Modelling the progressive services separately can alone account for 30% of the income effects

Human Attention in Image Captioning: Dataset and Analysis

In this work, we present a novel dataset consisting of eye movements and verbal descriptions recorded synchronously over images. Using this data, we study the differences in human attention during free-viewing and image captioning tasks. We look into the relationship between human attention and language constructs during perception and sentence articulation. We also analyse attention deployment mechanisms in the top-down soft attention approach that is argued to mimic human attention in captioning tasks, and investigate whether visual saliency can help image captioning. Our study reveals that (1) human attention behaviour differs in free-viewing and image description tasks. Humans tend to fixate on a greater variety of regions under the latter task, (2) there is a strong relationship between described objects and attended objects ($97\%$ of the described objects are being attended), (3) a convolutional neural network as feature encoder accounts for human-attended regions during image captioning to a great extent (around $78\%$), (4) soft-attention mechanism differs from human attention, both spatially and temporally, and there is low correlation between caption scores and attention consistency scores. These indicate a large gap between humans and machines in regards to top-down attention, and (5) by integrating the soft attention model with image saliency, we can significantly improve the model's performance on Flickr30k and MSCOCO benchmarks. The dataset can be found at: https://github.com/SenHe/Human-Attention-in-Image-Captioning.Comment: To appear at ICCV 201