10,096 research outputs found
Sketch-based Influence Maximization and Computation: Scaling up with Guarantees
Propagation of contagion through networks is a fundamental process. It is
used to model the spread of information, influence, or a viral infection.
Diffusion patterns can be specified by a probabilistic model, such as
Independent Cascade (IC), or captured by a set of representative traces.
Basic computational problems in the study of diffusion are influence queries
(determining the potency of a specified seed set of nodes) and Influence
Maximization (identifying the most influential seed set of a given size).
Answering each influence query involves many edge traversals, and does not
scale when there are many queries on very large graphs. The gold standard for
Influence Maximization is the greedy algorithm, which iteratively adds to the
seed set a node maximizing the marginal gain in influence. Greedy has a
guaranteed approximation ratio of at least (1-1/e) and actually produces a
sequence of nodes, with each prefix having approximation guarantee with respect
to the same-size optimum. Since Greedy does not scale well beyond a few million
edges, for larger inputs one must currently use either heuristics or
alternative algorithms designed for a pre-specified small seed set size.
We develop a novel sketch-based design for influence computation. Our greedy
Sketch-based Influence Maximization (SKIM) algorithm scales to graphs with
billions of edges, with one to two orders of magnitude speedup over the best
greedy methods. It still has a guaranteed approximation ratio, and in practice
its quality nearly matches that of exact greedy. We also present influence
oracles, which use linear-time preprocessing to generate a small sketch for
each node, allowing the influence of any seed set to be quickly answered from
the sketches of its nodes.Comment: 10 pages, 5 figures. Appeared at the 23rd Conference on Information
and Knowledge Management (CIKM 2014) in Shanghai, Chin
Shaping Social Activity by Incentivizing Users
Events in an online social network can be categorized roughly into endogenous
events, where users just respond to the actions of their neighbors within the
network, or exogenous events, where users take actions due to drives external
to the network. How much external drive should be provided to each user, such
that the network activity can be steered towards a target state? In this paper,
we model social events using multivariate Hawkes processes, which can capture
both endogenous and exogenous event intensities, and derive a time dependent
linear relation between the intensity of exogenous events and the overall
network activity. Exploiting this connection, we develop a convex optimization
framework for determining the required level of external drive in order for the
network to reach a desired activity level. We experimented with event data
gathered from Twitter, and show that our method can steer the activity of the
network more accurately than alternatives
Geometric picture of quantum discord for two-qubit quantum states
Among various definitions of quantum correlations, quantum discord has
attracted considerable attention. To find analytical expression of quantum
discord is an intractable task. Exact results are known only for very special
states, namely, two-qubit X-shaped states. We present in this paper a geometric
viewpoint, from which two-qubit quantum discord can be described clearly. The
known results about X state discord are restated in the directly perceivable
geometric language. As a consequence, the dynamics of classical correlations
and quantum discord for an X state in the presence of decoherence is endowed
with geometric interpretation. More importantly, we extend the geometric method
to the case of more general states, for which numerical as well as analytica
results about quantum discord have not been found yet. Based on the support of
numerical computations, some conjectures are proposed to help us establish
geometric picture. We find that the geometric picture for these states has
intimate relationship with that for X states. Thereby in some cases analytical
expressions of classical correlations and quantum discord can be obtained.Comment: 9 figure
Disentangling effects of nuclear structure in heavy element formation
Forming the same heavy compound nucleus with different isotopes of the projectile and target elements
allows nuclear structure effects in the entrance channel (resulting in static deformation) and in the
dinuclear system to be disentangled. Using three isotopes of Ti and W, forming 232Cm, with measurement
spanning the capture barrier energies, alignment of the heavy prolate deformed nucleus is shown to be the
main reason for the broadening of the mass distribution of the quasifission fragments as the beam energy is
reduced. The complex, consistently evolving mass-angle correlations that are observed carry more
information than the integrated mass or angular distributions, and should severely test models of
quasifission
An extended model to support detailed GPGPU reliability analysis
General Purpose Graphics Processing Units (GPGPUs) have been used in the last decades as accelerators in high demanding data processing applications, such as multimedia processing and high-performance computing. Nowadays, these devices are becoming popular even in safety-critical applications, such as autonomous and semi-autonomous vehicles. However, these devices can suffer from the effects of transient faults, such as those produced by radiation effects. These effects can be represented in the system as Single Event Upsets (SEUs) and are able to generate intolerable application misbehaviors in safety critical environments. In this work, we extended the capabilities of an open-source VHDL GPGPU model (FlexGrip) in order to study and analyze in a much more detailed manner the effects of SEUs in some critical modules within a GPGPU. Simulation results showed that scheduler controller has different levels of SEU sensibility depending on the affected location. Moreover, a reduced number of execution units, in the GPGPU can decrease the system reliability
Methane storms as a driver of Titan's dune orientation
Titan's equatorial regions are covered by eastward propagating linear dunes.
This direction is opposite to mean surface winds simulated by Global Climate
Models (GCMs), which are oriented westward at these latitudes, similar to trade
winds on Earth. Different hypotheses have been proposed to address this
apparent contradiction, involving Saturn's gravitational tides, large scale
topography or wind statistics, but none of them can explain a global eastward
dune propagation in the equatorial band. Here we analyse the impact of
equinoctial tropical methane storms developing in the superrotating atmosphere
(i.e. the eastward winds at high altitude) on Titan's dune orientation. Using
mesoscale simulations of convective methane clouds with a GCM wind profile
featuring superrotation, we show that Titan's storms should produce fast
eastward gust fronts above the surface. Such gusts dominate the aeolian
transport, allowing dunes to extend eastward. This analysis therefore suggests
a coupling between superrotation, tropical methane storms and dune formation on
Titan. Furthermore, together with GCM predictions and analogies to some
terrestrial dune fields, this work provides a general framework explaining
several major features of Titan's dunes: linear shape, eastward propagation and
poleward divergence, and implies an equatorial origin of Titan's dune sand.Comment: Published online on Nature Geoscience on 13 April 201
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks
A typical viral marketing model identifies influential users in a social network to maximize a single product adoption assuming unlimited user attention, campaign budgets, and time. In reality, multiple products need campaigns, users have limited attention, convincing users incurs costs, and advertisers have limited budgets and expect the adoptions to be maximized soon. Facing these user, monetary, and timing constraints, we formulate the problem as a submodular maximization task in a continuous-time diffusion model under the intersection of a matroid and multiple knapsack constraints. We propose a randomized algorithm estimating the user influence in a network ( nodes, edges) to an accuracy of with randomizations and computations. By exploiting the influence estimation algorithm as a subroutine, we develop an adaptive threshold greedy algorithm achieving an approximation factor of the optimal when out of the knapsack constraints are active. Extensive experiments on networks of millions of nodes demonstrate that the proposed algorithms achieve the state-of-the-art in terms of effectiveness and scalability
Distilling Information Reliability and Source Trustworthiness from Digital Traces
Online knowledge repositories typically rely on their users or dedicated
editors to evaluate the reliability of their content. These evaluations can be
viewed as noisy measurements of both information reliability and information
source trustworthiness. Can we leverage these noisy evaluations, often biased,
to distill a robust, unbiased and interpretable measure of both notions?
In this paper, we argue that the temporal traces left by these noisy
evaluations give cues on the reliability of the information and the
trustworthiness of the sources. Then, we propose a temporal point process
modeling framework that links these temporal traces to robust, unbiased and
interpretable notions of information reliability and source trustworthiness.
Furthermore, we develop an efficient convex optimization procedure to learn the
parameters of the model from historical traces. Experiments on real-world data
gathered from Wikipedia and Stack Overflow show that our modeling framework
accurately predicts evaluation events, provides an interpretable measure of
information reliability and source trustworthiness, and yields interesting
insights about real-world events.Comment: Accepted at 26th World Wide Web conference (WWW-17
Programmers manual FlexGripPlus SASS SM 1.0
This document describes the op-code of the assembly language SASS of the G80 architecture used in the FlexGripPlus model. Every instruction is compatible with the CUDA Programming environment under the SM_1.
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