Computer Science

New data on the age, composition, formation conditions, and ore-geochemical specialization of the Nui Chua layered peridotite-gabbro complex are reported. They evidence that the complex resulted from the Permo-Triassic mantle plume activity in northern Vietnam (southern framing of the Yangtze Platform). Two series of mafic and ultramafic rocks differing in ore productivity-layered (PGE-Cu-Ni) and pegmatoid (Fe-Ti-V)-have been recognized within the complex. The first estimates of the composition of their parental melts have been obtained.

The real social network and associated communities are
often hidden under the declared friend or group lists in
social networks. We usually observe the manifestation
of these hidden networks and communities in the form
of recurrent and time-stamped individuals' activities in
the social network. Inferring the underlying network
and nding coherent communities are therefore two key
challenges in social networks analysis.
In this paper, we address the following question:
Could we simultaneously detect community structure
and network infectivity among individuals from their ac-
tivities? Based on the fact that the two characteristics
intertwine and that knowing one will help better reveal-
ing the other, we propose a multidimensional Hawkes
process that can address them simultaneously. To this
end, we parametrize the network infectivity in terms of
individuals' participation in communities and the pop-
ularity of each individual. We show that this modeling
approach has many benets, both conceptually and ex-
perimentally. We utilize Bayesian variational inference
to design NetCodec, an ecient inference algorithm
which is veried with both synthetic and real world
data sets. The experiments show that NetCodec can
discover the underlying network infectivity and commu-
nity structure more accurately than baseline method.

The recent adoption of the Robot Operating System (ROS) as a software standard in robotics has contributed to novel solutions for several problems on the area. One such problem is known as Simultaneous Localization and Mapping (SLAM), for which a number of algorithms from different classes are available as ROS packages ready to be used on any compatible robot. Considering that there is often a need to evaluate and choose an appropriate solution in any robotics application, this work presents an experimental evaluation of five SLAM algorithms usable on RGB-D sensors, namely, Gmapping, Hector SLAM, ORB SLAM, ORB SLAM 2 and RTAB-Map. The algorithms are assessed on data depicting realistic operation scenarios according to established criteria enumerated to emphasize practical aspects of the selected systems. The experiences reported on this work should provide insight for roboticists seeking a SLAM solution for indoor applications.

The Alternating Direction Method of Multipliers (ADMM) has received lots of attention recently due to the tremendous demand from large-scale and data-distributed machine learning applications. In this paper, we present a stochastic setting for optimization problems with non-smooth composite objective functions. To solve this problem, we propose a stochastic ADMM algorithm. Our algorithm applies to a more general class of convex and nonsmooth objective functions, beyond the smooth and separable least squares loss used in lasso. We also demonstrate the rates of convergence for our algorithm under various structural assumptions of the stochastic function: O(1/√t)) for convex functions and O(log t/t) for strongly convex functions. Compared to previous literature, we establish the convergence rate of ADMM for convex problems in terms of both the objective value and the feasibility violation. A novel application named Graph-Guided SVM is proposed to demonstrate the usefulness of our algor...