Efficient File Synchronization: a Distributed Source Coding Approach

The problem of reconstructing a source sequence with the presence of decoder side-information that is mis-synchronized to the source due to deletions is studied in a distributed source coding framework. Motivated by practical applications, the deletion process is assumed to be bursty and is modeled by a Markov chain. The minimum rate needed to reconstruct the source sequence with high probability is characterized in terms of an information theoretic expression, which is interpreted as the amount of information of the deleted content and the locations of deletions, subtracting "nature's secret", that is, the uncertainty of the locations given the source and side-information. For small bursty deletion probability, the asymptotic expansion of the minimum rate is computed.Comment: 9 pages, 2 figures. A shorter version will appear in IEEE International Symposium on Information Theory (ISIT), 201

Polynomial-time Tensor Decompositions with Sum-of-Squares

We give new algorithms based on the sum-of-squares method for tensor decomposition. Our results improve the best known running times from quasi-polynomial to polynomial for several problems, including decomposing random overcomplete 3-tensors and learning overcomplete dictionaries with constant relative sparsity. We also give the first robust analysis for decomposing overcomplete 4-tensors in the smoothed analysis model. A key ingredient of our analysis is to establish small spectral gaps in moment matrices derived from solutions to sum-of-squares relaxations. To enable this analysis we augment sum-of-squares relaxations with spectral analogs of maximum entropy constraints.Comment: to appear in FOCS 201

Environmental and Ecological Economics: A Citation Analysis

This study looks at two distinct questions: What have been the most influential journal articles in environmental economics over the ten year period 1994-2003? and, how much overlap is there between the fields of environmental and ecological economics? We examine the references in all articles published in JEEM and Ecological Economics (EE) over this period. For each of these two fields, a list of the top articles and top journals cited by articles published in JEEM and EE is presented. We also present some results based on our study of the ISI Journal Citation Reports. We find that there is a significant overlap between the two fields at the journal level - the two journals cite similar journals. There is a correlation of 0.34 between the number of citations received by the journals that are most cited and the correlation is even higher if journal self-citation is excluded. The main differences are that ecological economics tends to cite (but not be cited by) general natural science journals more often than environmental economics does, environmental economics cites more heavily from journals rather than other publications, and citations in environmental economics are more concentrated on particular journals and individual publications. However, there is much less similarity at the level of individual articles. Non-market valuation articles dominate the most cited articles in JEEM while green accounting, sustainability, and environmental Kuznets curve are all prominent topics in EE.

Some combinatorial arrays related to the Lotka-Volterra system

The purpose of this paper is to investigate the connection between the Lotka-Volterra system and combinatorics. We study several context-free grammars associated with the Lotka-Volterra system. Some combinatorial arrays, involving the Stirling numbers of the second kind and Eulerian numbers, are generated by these context-free grammars. In particular, we present grammatical characterization of some statistics on cyclically ordered partitions.Comment: 15 page

China's Changing Energy Intensity Trend: A Decomposition Analysis

China experienced a dramatic decline in energy intensity from the onset of economic reform in the late 1970s until 2000, but since then rate of decline slowed and energy intensity actually increased in 2003. Most previous studies found that most of the decline was due to technological change, but disagreed on the role of structural change. To the best of our knowledge, no decomposition study has investigated the role of inter-fuel substitution in the decline in energy intensity or the causes of the rise in energy intensity since 2000. In this paper, we use logarithmic mean Divisia index (LMDI) techniques to decompose changes in energy intensity in the period 1980-2003. We find that: (1) technological change is confirmed as the dominant contributor to the decline in energy intensity; (2) structural change at the industry and sector (sub-industry) level actually increased energy intensity over the period of 1980-2003, although the structural change at the industry level was very different in the 1980s and in the post 1990 period; (3) structural change involving shifts of production between sub-sectors, however, decreased overall energy intensity; (4) the increase in energy intensity since 2000 is explained by negative technological progress; (5) inter-fuel substitution is found to contribute little to the changes in energy intensity.