A note on a system of parameters
Let $u$ be in $\mathfrak{p}\in\mathrm{Assh}(R)$. We present several situations for which $(0 : u)$ is (not) in an ideal generated by a system of parameters. An application is given....
A Measure of the Goodness of Fit in Unbinned Likelihood Fits; End of Bayesianism…
Maximum likelihood fits to data can be done using binned data (histograms) and unbinned data. With binned data, one gets not only the fitted parameters but also a measure of the goodness of fit. With unbinned data, currently, the fitted parameters...
A Measure of the Goodness of Fit in Unbinned Likelihood Fits
Maximum likelihood fits to data can be done using binned data (histograms) and unbinned data. With binned data, one gets not only the fitted parameters but also a measure of the goodness of fit. With unbinned data, currently, the fitted parameters...
AnubisGott/BDSMSessionCreator
This Android App helps people to create a BDSM session. Input parameters are how much time is available and your preferences. With this input parameters a random session is created. (⭐ 14)
A catalogue of low-mass X-ray binaries in the Galaxy, LMC, and SMC (Fourth editi…
We present a new edition of the catalogue of the low-mass X-ray binaries in the Galaxy and the Magellanic Clouds. The catalogue contains source name(s), coordinates, finding chart, X-ray luminosity, system parameters, and stellar parameters of the...
A disciplined approach to neural network hyper-parameters: Part 1 -- learning ra…
Although deep learning has produced dazzling successes for applications of image, speech, and video processing in the past few years, most trainings are with suboptimal hyper-parameters, requiring unnecessarily long training times. Setting the hyper-...
Learning Optimal Parameters for Multi-target Tracking with Contextual Interactio…
We describe an end-to-end framework for learning parameters of min-cost flow multi-target tracking problem with quadratic trajectory interactions including suppression of overlapping tracks and contextual cues about cooccurrence of different objects....
Optimization of Geometric Constellation Shaping for Wiener Phase Noise Channels…
We present a novel method to investigate the effects of varying channel parameters on geometrically shaped constellations for communication systems employing the blind phase search algorithm. We show that introduced asymmetries significantly improve...
Investigating the Optimal Neural Network Parameters for Decoding
Neural Networks have been proved to work as decoders in telecommunications, so the ways of making it efficient will be investigated in this thesis. The different parameters to maximize the Neural Network Decoder's efficiency will be investigated. The...
Real analyticity of accessory parameters
We consider the problem of the real analytic dependence of the accessory parameters of Liouville theory on the moduli of the problem, for general elliptic singularities. We give a simplified proof of the almost everywhere real analyticity in the case...
Parameters Tied to Treewidth
Treewidth is a graph parameter of fundamental importance to algorithmic and structural graph theory. This paper surveys several graph parameters tied to treewidth, including separation number, tangle number, well-linked number and Cartesian tree prod...
A Particular Collection of Service Time Distributions Parameters Study and Impac…
The problems arising when the moments of service time distributions, for which the MGinf queue system busy period and busy cycle become very easy to study, are presented and it is shown how to overcome them. The busy cycle renewal function and the pe...
PyEPO: A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and I…
In deterministic optimization, it is typically assumed that all problem parameters are fixed and known. In practice, however, some parameters may be a priori unknown but can be estimated from historical data. A typical predict-then-optimize approach...
Quantified HI Morphology VII: star-formation and tidal influence on local dwarf…
Scale-invariant morphology parameters applied to atomic hydrogen maps (HI) of galaxies can be used to quantify the effects of tidal interaction or star-formation on the ISM. Here we apply these parameters, Concentration, Asymmetry, Smoothness, Gini,...
Monte Carlo Confidence Sets for Identified Sets
In complicated/nonlinear parametric models, it is generally hard to know whether the model parameters are point identified. We provide computationally attractive procedures to construct confidence sets (CSs) for identified sets of full parameters and...
Grey Power Models Based on Optimization of Initial Condition and Model Parameter…
We propose a novel approach to improve prediction accuracy of grey power models including GM(1,1) and grey Verhulst model through optimization of the initial condition and model parameters in this paper. And we propose a modified grey Verhulst model....
Boxing with Neutrino Oscillations
We develop a model-independent "box" parameterization of neutrino oscillations. Oscillation probabilities are linear in these new parameters, so measurements can straightforwardly determine the box parameters which can then be manipulated to yield...
Slim PHP and GET Parameters
Tags: php, rest, slim | Score: 67
NeuroGen: Neural Network Parameter Generation via Large Language Models
Acquiring the parameters of neural networks (NNs) has been one of the most important problems in machine learning since the inception of NNs. Traditional approaches, such as backpropagation and forward-only optimization, acquire parameters via iterat...
Determination of the CKM unitarity triangle parameters by end 1999
Within the Standard Model, a review of the current determination of the CKM unitarity triangle parameters is presented, using experimental constraints from the measurements of |epsilon_K|, V_ub/V_cb, Delta m_d and from the limit on Delta m_s, avail...