New ML models improve VVLC channel characterization for vehicular OWC.
arXiv research
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Optimizes UAV deployment for VLC-enabled UAVs considering illumination distribution.
In this paper, we investigate the design and implementation of machine learning (ML) based demodulation methods in the physical layer of visible light communication (VLC) systems. We build a flexible hardware prototype of an end-to-end VLC system, from which the received signals are collected as the real data. The data…
Measuring supernova neutrinos removes spacetime's conformal freedom.
Paper proposes a graph model for optimal AP deployment in indoor optical wireless networks.
Paper tackles image recovery from blurry measurements using deep generative priors.
In a densely populated city like Dhaka (Bangladesh), a growing number of high-rise buildings is an inevitable reality. However, they pose mental health risks for citizens in terms of detachment from natural light, sky view, greenery, and environmental landscapes. The housing economy and rent structure in different area…
Designs chiral photonic structures using machine learning for efficient optical properties.
A multiple classifiers fusion localization technique using received signal strengths (RSSs) of visible light is proposed, in which the proposed system transmits different intensity modulated sinusoidal signals by LEDs and the signals received by a Photo Diode (PD) placed at various grid points. First, we obtain some {\…
Study uses cGAN to translate multispectral to nighttime satellite imagery.
Visible Lagrangians in Hitchin systems are studied for pillowcase covers.
NCV uses neural networks to improve Monte Carlo integration.
Characterizes visibility and geodesic loops in complex domains.
Study visibility properties of Kobayashi distance on unbounded domains.
We show that the translation length of any parabolic isometry on a complete semi-uniformly visible CAT(0) space is always zero. As a consequence, we will classify the isometries on visible CAT(0) spaces in terms of translation lengths. We will also show that the moduli space of surface o…
Mathematical framework for cooperative communication explains belief transmission.
Recently, the visibility graph has been introduced as a novel view for analyzing time series, which maps it to a complex network. In this paper, we introduce new algorithm of visibility, "cross-visibility", which reveals the conjugation of two coupled time series. The correspondence between the two time series is mappe…
This article is devoted to the study of prime alternating +achiral knots. In the case of arborescent knots, we prove in +AAA Visibility Theorem 5.1, that the symmetry is visible on a certain projection (not necessarily minimal) and that it is realised by a homeomorphism of order 4. In the general case (arborescent or n…
Improved visibility forecasts using statistical post-processing.
The visibility transformation embeds data position into signature features for efficient pattern recognition.
With the advent of GDPR, the domain of explainable AI and model interpretability has gained added impetus. Methods to extract and communicate visibility into decision-making models have become legal requirement. Two specific types of explanations, contrastive and counterfactual have been identified as suitable for huma…
The family of image visibility graphs (IVGs) have been recently introduced as simple algorithms by which scalar fields can be mapped into graphs. Here we explore the usefulness of such operator in the scenario of image processing and image classification. We demonstrate that the link architecture of the image visibilit…
The study shows that the visible range from a point on harmonic manifolds follows an exponential distribution.
We study relations of some classes of -convex, -visible bodies in Euclidean spaces. We introduce and study \textrm{circular projections} in normed linear spaces and classes of bodies related with families of such maps, in particular, \textrm{-circular convex} and \textrm{-circular visible} ones. Investigati…
With millimeter wave wireless communications, the resulting radiation reflects on most visible objects, creating rich multipath environments, namely in urban scenarios. The radiation captured by a listening device is thus shaped by the obstacles encountered, which carry latent information regarding their relative posit…
A visible action on a complex manifold is a holomorphic action that admits a -transversal totally real submanifold . It is said to be strongly visible if there exists an orbit-preserving anti-holomorphic diffeomorphism such that . In this paper, we prove that for any Hermitian symmetric sp…
We show that complete uniform visibility manifolds of finite volume with sectional curvature have positive simplicial volumes. This implies that their minimal volumes are non-zero.
Paper proposes AggITD for efficient federated hypergradient computation.
The paper analyzes generalization of noisy iterative algorithms using communication theory.
We show that the visible sector probability density function of the Riemann-Theta Boltzmann machine corresponds to a gaussian mixture model consisting of an infinite number of component multi-variate gaussians. The weights of the mixture are given by a discrete multi-variate gaussian over the hidden state space. This a…
The paper connects geodesic flows and limit sets on visibility manifolds.
In the age of globalization, it is natural that the stock market of each country is not independent form the other markets. In this case, collective behavior could be emerged form their dependency together. This article studies the collective behavior of a set of forty influential markets in the world economy with the …
GNNs robustness in community detection is studied with various perturbations.
Enhances nighttime vehicle detection using style transfer and augmentation.
Study on visibility properties of spiral sets in higher dimensions.
Paper uses SDP for community detection with side information.
Structural RBM reduces parameters for image denoising and classification.
New optimization for federated learning with local models.
Characterizes causal structure dominance for latent variables.
We present a technique for efficiently synthesizing images of atmospheric clouds using a combination of Monte Carlo integration and neural networks. The intricacies of Lorenz-Mie scattering and the high albedo of cloud-forming aerosols make rendering of clouds---e.g. the characteristic silverlining and the "whiteness" …
Extends curvature results to manifolds with close-to-zero curvature.
The investigations of financial markets from a complex network perspective have unveiled many phenomenological properties, in which the majority of these studies map the financial markets into one complex network. In this work, we investigate 30 world stock market indices through their visibility graphs by adopting the…
Extends partitioned local depth concept with probabilistic considerations.
Enhanced visibility forecasts using CAMS data improve accuracy.
The performance and efficiency of distributed machine learning (ML) depends significantly on how long it takes for nodes to exchange state changes. Overly-aggressive attempts to reduce communication often sacrifice final model accuracy and necessitate additional ML techniques to compensate for this loss, limiting their…
Proposes COLA, a communication-efficient algorithm for decentralized optimization.
Sunshine trading theory predicts lower execution costs and liquidity provision through explicit preannouncements, but evidence is scarce in traditional markets.
Multi-view data are becoming common in real-world modeling tasks and many multi-view data clustering algorithms have thus been proposed. The existing algorithms usually focus on the cooperation of different views in the original space but neglect the influence of the hidden information among these different visible vie…