Coordination and Efficiency in Decentralized Collaboration

Environments for decentralized on-line collaboration are now widespread on the Web, underpinning open-source efforts, knowledge creation sites including Wikipedia, and other experiments in joint production. When a distributed group works together in such a setting, the mechanisms they use for coordination can play an important role in the effectiveness of the group's performance. Here we consider the trade-offs inherent in coordination in these on-line settings, balancing the benefits to collaboration with the cost in effort that could be spent in other ways. We consider two diverse domains that each contain a wide range of collaborations taking place simultaneously -- Wikipedia and GitHub -- allowing us to study how coordination varies across different projects. We analyze trade-offs in coordination along two main dimensions, finding similar effects in both our domains of study: first we show that, in aggregate, high-status projects on these sites manage the coordination trade-off at a different level than typical projects; and second, we show that projects use a different balance of coordination when they are "crowded," with relatively small size but many participants. We also develop a stylized theoretical model for the cost-benefit trade-off inherent in coordination and show that it qualitatively matches the trade-offs we observe between crowdedness and coordination.Comment: 10 pages, 6 figures, ICWSM 2015, in Proc. 9th International AAAI Conference on Weblogs and Social Medi

Worldwide Pose Estimation Using 3D Point Clouds

We address the problem of determining where a photo was taken by estimating a full 6-DOF-plus-intrincs camera pose with respect to a large geo-registered 3D point cloud, bringing together research on image localization, landmark recognition, and 3D pose estimation. Our method scales to datasets with hundreds of thousands of images and tens of millions of 3D points through the use of two new techniques: a co-occurrence prior for RANSAC and bidirectional matching of image features with 3D points. We evaluate our method on several large data sets, and show state-of-the-art results on landmark recognition as well as the ability to locate cameras to within meters, requiring only seconds per query

Variant of TREM2 associated with the risk of Alzheimer's disease.

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.BACKGROUND: Sequence variants, including the ε4 allele of apolipoprotein E, have been associated with the risk of the common late-onset form of Alzheimer's disease. Few rare variants affecting the risk of late-onset Alzheimer's disease have been found. METHODS: We obtained the genome sequences of 2261 Icelanders and identified sequence variants that were likely to affect protein function. We imputed these variants into the genomes of patients with Alzheimer's disease and control participants and then tested for an association with Alzheimer's disease. We performed replication tests using case-control series from the United States, Norway, The Netherlands, and Germany. We also tested for a genetic association with cognitive function in a population of unaffected elderly persons. RESULTS: A rare missense mutation (rs75932628-T) in the gene encoding the triggering receptor expressed on myeloid cells 2 (TREM2), which was predicted to result in an R47H substitution, was found to confer a significant risk of Alzheimer's disease in Iceland (odds ratio, 2.92; 95% confidence interval [CI], 2.09 to 4.09; P=3.42×10(-10)). The mutation had a frequency of 0.46% in controls 85 years of age or older. We observed the association in additional sample sets (odds ratio, 2.90; 95% CI, 2.16 to 3.91; P=2.1×10(-12) in combined discovery and replication samples). We also found that carriers of rs75932628-T between the ages of 80 and 100 years without Alzheimer's disease had poorer cognitive function than noncarriers (P=0.003). CONCLUSIONS: Our findings strongly implicate variant TREM2 in the pathogenesis of Alzheimer's disease. Given the reported antiinflammatory role of TREM2 in the brain, the R47H substitution may lead to an increased predisposition to Alzheimer's disease through impaired containment of inflammatory processes. (Funded by the National Institute on Aging and others.).Research Council of NorwayNational Institute on Aging P50-AG025688 U01AG006781South-Eastern Norway Health AuthorityNational Institutes of Health U01HG004438National Human Genome Research Institute U01HG004610eMERGE Administrative Coordinating Center U01HG004603National Center for Biotechnology InformationErasmus Medical CenterErasmus University, RotterdamNetherlands Organization for Health Research and DevelopmentResearch Institute for Diseases in the ElderlyMinistry of Education, Culture and ScienceMinistry for Health, Welfare and SportsMunicipality of RotterdamResearch Institute for Diseases in the Elderly 014-93-015Stichting Alzheimer Onder-zoekHersenstichting NederlandNetherlands Genomics Initiative-Netherlands Organization for Scientific Research (Center for Medical Systems Biology and the Netherlands Consortium for Healthy Aging)info:eu-repo/grantAgreement/EC/FP7/20141

Discrete-continuous optimization for large-scale structure from motion

Recent work in structure from motion (SfM) has successfully built 3D models from large unstructured collections of images downloaded from the Internet. Most approaches use incremental algorithms that solve progressively larger bundle adjustment problems. These incremental techniques scale poorly as the number of images grows, and can drift or fall into bad local minima. We present an alternative formulation for SfM based on finding a coarse initial solution using a hybrid discrete-continuous optimization, and then improving that solution using bundle adjustment. The initial optimization step uses a discrete Markov random field (MRF) formulation, coupled with a continuous Levenberg-Marquardt refinement. The formulation naturally incorporates various sources of information about both the cameras and the points, including noisy geotags and vanishing point estimates. We test our method on several large-scale photo collections, including one with measured camera positions, and show that it can produce models that are similar to or better than those produced with incremental bundle adjustment, but more robustly and in a fraction of the time. 1

Fast Detection of Common Geometric Substructure in Proteins

We consider the problem of identifying common three-dimensional substructures between proteins. Our method is based on comparing the shape of the ff-carbon backbone structures of the proteins in order to find 3D rigid motions that bring portions of the geometric structures into correspondence. We propose a geometric representation of protein backbone chains that is compact yet allows for similarity measures that are robust against noise and outliers. We represent the structure of the backbone as a sequence of unit vectors, defined by each adjacent pair of ff-carbons; we then define a measure of the similarity of two protein structures based on the RMS (root mean squared) distance between corresponding orientation vectors of the two proteins

Fast Detection of Common Geometric Substructure in Proteins

We consider the problem of identifying common three-dimensional substructures between proteins. Our method is based on comparing the shape of the #-carbon backbone structures of the proteins in order to find 3D rigid motions that bring portions of the geometric structures into correspondence. We propose a geometric representation of protein backbone chains that is compact yet allows for similarity measures that are robust against noise and outliers. We represent the structure of the backbone as a sequence of unit vectors, defined by each adjacent pair of #-carbons; we then define a measure of the similarity of two protein structures based on the RMS (root mean squared) distance between corresponding orientation vectors of the two proteins

Group Formation in Large Social Networks: Membership, Growth, and Evolution

The processes by which communities come together, attract new members, and develop over time is a central research issue in the social sciences — political movements, professional organizations, and religious denominations all provide fundamental examples of such communities. In the digital domain, on-line groups are becoming increasingly prominent due to the growth of community and social networking sites such as MySpace and LiveJournal. However, the challenge of collecting and analyzing large-scale timeresolved data on social groups and communities has left most basic questions about the evolution of such groups largely unresolved: what are the structural features that influence whether individuals will join communities, which communities will grow rapidly, and how do the overlaps among pairs of communities change over time? Here we address these questions using two large sources of data