11,426 research outputs found
Optimal learning with -aggregation
We consider a general supervised learning problem with strongly convex and
Lipschitz loss and study the problem of model selection aggregation. In
particular, given a finite dictionary functions (learners) together with the
prior, we generalize the results obtained by Dai, Rigollet and Zhang [Ann.
Statist. 40 (2012) 1878-1905] for Gaussian regression with squared loss and
fixed design to this learning setup. Specifically, we prove that the
-aggregation procedure outputs an estimator that satisfies optimal oracle
inequalities both in expectation and with high probability. Our proof
techniques somewhat depart from traditional proofs by making most of the
standard arguments on the Laplace transform of the empirical process to be
controlled.Comment: Published in at http://dx.doi.org/10.1214/13-AOS1190 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Uniqueness domains and non singular assembly mode changing trajectories
Parallel robots admit generally several solutions to the direct kinematics
problem. The aspects are associated with the maximal singularity free domains
without any singular configurations. Inside these regions, some trajectories
are possible between two solutions of the direct kinematic problem without
meeting any type of singularity: non-singular assembly mode trajectories. An
established condition for such trajectories is to have cusp points inside the
joint space that must be encircled. This paper presents an approach based on
the notion of uniqueness domains to explain this behaviour
Twin-screw extrusion impact on natural fibre morphology and material properties in poly(lactic acid) based biocomposites
Natural fibres from miscanthus and bamboo were added to poly(lactic acid) by twin-screw extrusion. The influence of extruder screw speed and of total feeding rate was studied first on fibre morphology and then on mechanical and thermal properties of injected biocomposites. Increasing the screw speed from 100 to 300 rpm such as increasing the feeding rate in the same time up to 40 kg/h helped to preserve fibre length. Indeed, if shear rate was increased with higher screw speeds, residence time in the extruder and blend viscosity were reduced. However, such conditions doubled electrical energy spent by produced matter weight without significant effect on material properties.
The comparison of four bamboo grades with various fibre sizes enlightened that fibre breakages were more consequent when longer fibres were added in the extruder. Longer fibres were beneficial for material mechanical properties by increasing flexural strength, while short fibres restrained material deformation under heat by promoting crystallinity and hindering more chain mobility
Probing Strongly Coupled Chameleons with Slow Neutrons
We consider different methods to probe chameleons with slow neutrons.
Chameleon modify the potential of bouncing neutrons over a flat mirror in the
terrestrial gravitational field. This induces a shift in the energy levels of
the neutrons which could be detected in current experiments like GRANIT.
Chameleons between parallel plates have a field profile which is bubble-like
and which would modify the phase of neutrons in interferometric experiments. We
show that this new method of detection is competitive with the bouncing neutron
one, hopefully providing an efficient probe of chameleons when strongly coupled
to matter
Rheopexy and tunable yield stress of carbon black suspensions
We show that besides simple or thixotropic yield stress fluids there exists a
third class of yield stress fluids. This is illustrated through the rheological
behavior of a carbon black suspension, which is shown to exhibit a viscosity
bifurcation effect around a critical stress along with rheopectic trends, i.e.,
after a preshear at a given stress the fluid tends to accelerate when it is
submitted to a lower stress. Viscosity bifurcation displays here original
features: the yield stress and the critical shear rate depend on the previous
flow history. The most spectacular property due to these specificities is that
the material structure can be adjusted at will through an appropriate flow
history. In particular it is possible to tune the material yield stress to
arbitrary low values. A simple model assuming that the stress is the sum of one
component due to structure deformation and one component due to hydrodynamic
interactions predicts all rheological trends observed and appears to well
represent quantitatively the data.Comment: submitted to Soft Matte
Structured chaos shapes spike-response noise entropy in balanced neural networks
Large networks of sparsely coupled, excitatory and inhibitory cells occur
throughout the brain. A striking feature of these networks is that they are
chaotic. How does this chaos manifest in the neural code? Specifically, how
variable are the spike patterns that such a network produces in response to an
input signal? To answer this, we derive a bound for the entropy of multi-cell
spike pattern distributions in large recurrent networks of spiking neurons
responding to fluctuating inputs. The analysis is based on results from random
dynamical systems theory and is complimented by detailed numerical simulations.
We find that the spike pattern entropy is an order of magnitude lower than what
would be extrapolated from single cells. This holds despite the fact that
network coupling becomes vanishingly sparse as network size grows -- a
phenomenon that depends on ``extensive chaos," as previously discovered for
balanced networks without stimulus drive. Moreover, we show how spike pattern
entropy is controlled by temporal features of the inputs. Our findings provide
insight into how neural networks may encode stimuli in the presence of
inherently chaotic dynamics.Comment: 9 pages, 5 figure
Shear-induced sedimentation in yield stress fluids
Stability of coarse particles against gravity is an important issue in dense
suspensions (fresh concrete, foodstuff, etc.). On the one hand, it is known
that they are stable at rest when the interstitial paste has a high enough
yield stress; on the other hand, it is not yet possible to predict if a given
material will remain homogeneous during a flow. Using MRI techniques, we study
the time evolution of the particle volume fraction during the flows in a
Couette geometry of model density-mismatched suspensions of noncolloidal
particles in yield stress fluids. We observe that shear induces sedimentation
of the particles in all systems, which are stable at rest. The sedimentation
velocity is observed to increase with increasing shear rate and particle
diameter, and to decrease with increasing yield stress of the interstitial
fluid. At low shear rate ('plastic regime'), we show that this phenomenon can
be modelled by considering that the interstitial fluid behaves like a viscous
fluid -- of viscosity equal to the apparent viscosity of the sheared fluid --
in the direction orthogonal to shear. The behavior at higher shear rates, when
viscous effects start to be important, is also discussed. We finally study the
dependence of the sedimentation velocity on the particle volume fraction, and
show that its modelling requires estimating the local shear rate in the
interstitial fluid
Background subtraction based on Local Shape
We present a novel approach to background subtraction that is based on the
local shape of small image regions. In our approach, an image region centered
on a pixel is mod-eled using the local self-similarity descriptor. We aim at
obtaining a reliable change detection based on local shape change in an image
when foreground objects are moving. The method first builds a background model
and compares the local self-similarities between the background model and the
subsequent frames to distinguish background and foreground objects.
Post-processing is then used to refine the boundaries of moving objects.
Results show that this approach is promising as the foregrounds obtained are
com-plete, although they often include shadows.Comment: 4 pages, 5 figures, 3 tabl
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