6,212 research outputs found
Outlier robust corner-preserving methods for reconstructing noisy images
The ability to remove a large amount of noise and the ability to preserve
most structure are desirable properties of an image smoother. Unfortunately,
they usually seem to be at odds with each other; one can only improve one
property at the cost of the other. By combining M-smoothing and
least-squares-trimming, the TM-smoother is introduced as a means to unify
corner-preserving properties and outlier robustness. To identify edge- and
corner-preserving properties, a new theory based on differential geometry is
developed. Further, robustness concepts are transferred to image processing. In
two examples, the TM-smoother outperforms other corner-preserving smoothers. A
software package containing both the TM- and the M-smoother can be downloaded
from the Internet.Comment: Published at http://dx.doi.org/10.1214/009053606000001109 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
A tension approach to controlling the shape of cubic spline surfaces on FVS triangulations
We propose a parametric tensioned version of the FVS macro-element to control the shape of the composite surface and remove artificial oscillations, bumps and other undesired behaviour. In particular, this approach is applied to C1 cubic spline surfaces over a four-directional mesh produced by two-stage scattered data fitting methods
Agent-Based Simulations of Blockchain protocols illustrated via Kadena's Chainweb
While many distributed consensus protocols provide robust liveness and
consistency guarantees under the presence of malicious actors, quantitative
estimates of how economic incentives affect security are few and far between.
In this paper, we describe a system for simulating how adversarial agents, both
economically rational and Byzantine, interact with a blockchain protocol. This
system provides statistical estimates for the economic difficulty of an attack
and how the presence of certain actors influences protocol-level statistics,
such as the expected time to regain liveness. This simulation system is
influenced by the design of algorithmic trading and reinforcement learning
systems that use explicit modeling of an agent's reward mechanism to evaluate
and optimize a fully autonomous agent. We implement and apply this simulation
framework to Kadena's Chainweb, a parallelized Proof-of-Work system, that
contains complexity in how miner incentive compliance affects security and
censorship resistance. We provide the first formal description of Chainweb that
is in the literature and use this formal description to motivate our simulation
design. Our simulation results include a phase transition in block height
growth rate as a function of shard connectivity and empirical evidence that
censorship in Chainweb is too costly for rational miners to engage in. We
conclude with an outlook on how simulation can guide and optimize protocol
development in a variety of contexts, including Proof-of-Stake parameter
optimization and peer-to-peer networking design.Comment: 10 pages, 7 figures, accepted to the IEEE S&B 2019 conferenc
Downwash-Aware Trajectory Planning for Large Quadrotor Teams
We describe a method for formation-change trajectory planning for large
quadrotor teams in obstacle-rich environments. Our method decomposes the
planning problem into two stages: a discrete planner operating on a graph
representation of the workspace, and a continuous refinement that converts the
non-smooth graph plan into a set of C^k-continuous trajectories, locally
optimizing an integral-squared-derivative cost. We account for the downwash
effect, allowing safe flight in dense formations. We demonstrate the
computational efficiency in simulation with up to 200 robots and the physical
plausibility with an experiment with 32 nano-quadrotors. Our approach can
compute safe and smooth trajectories for hundreds of quadrotors in dense
environments with obstacles in a few minutes.Comment: 8 page
Joint Total Variation ESTATICS for Robust Multi-Parameter Mapping
Quantitative magnetic resonance imaging (qMRI) derives tissue-specific
parameters -- such as the apparent transverse relaxation rate R2*, the
longitudinal relaxation rate R1 and the magnetisation transfer saturation --
that can be compared across sites and scanners and carry important information
about the underlying microstructure. The multi-parameter mapping (MPM) protocol
takes advantage of multi-echo acquisitions with variable flip angles to extract
these parameters in a clinically acceptable scan time. In this context,
ESTATICS performs a joint loglinear fit of multiple echo series to extract R2*
and multiple extrapolated intercepts, thereby improving robustness to motion
and decreasing the variance of the estimators. In this paper, we extend this
model in two ways: (1) by introducing a joint total variation (JTV) prior on
the intercepts and decay, and (2) by deriving a nonlinear maximum \emph{a
posteriori} estimate. We evaluated the proposed algorithm by predicting
left-out echoes in a rich single-subject dataset. In this validation, we
outperformed other state-of-the-art methods and additionally showed that the
proposed approach greatly reduces the variance of the estimated maps, without
introducing bias.Comment: 11 pages, 2 figures, 1 table, conference paper, accepted at MICCAI
202
Frictional Unemployment on Labor Flow Networks
We develop an alternative theory to the aggregate matching function in which
workers search for jobs through a network of firms: the labor flow network. The
lack of an edge between two companies indicates the impossibility of labor
flows between them due to high frictions. In equilibrium, firms' hiring
behavior correlates through the network, generating highly disaggregated local
unemployment. Hence, aggregation depends on the topology of the network in
non-trivial ways. This theory provides new micro-foundations for the Beveridge
curve, wage dispersion, and the employer-size premium. We apply our model to
employer-employee matched records and find that network topologies with
Pareto-distributed connections cause disproportionately large changes on
aggregate unemployment under high labor supply elasticity
Quantum Shock Waves - the case for non-linear effects in dynamics of electronic liquids
Using the Calogero model as an example, we show that the transport in
interacting non-dissipative electronic systems is essentially non-linear.
Non-linear effects are due to the curvature of the electronic spectrum near the
Fermi energy. As is typical for non-linear systems, propagating wave packets
are unstable. At finite time shock wave singularities develop, the wave packet
collapses, and oscillatory features arise. They evolve into regularly
structured localized pulses carrying a fractionally quantized charge - {\it
soliton trains}. We briefly discuss perspectives of observation of Quantum
Shock Waves in edge states of Fractional Quantum Hall Effect and a direct
measurement of the fractional charge
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