We present a new adaptation method MaCP, Minimal yet Mighty adaptive Cosine Projection, that achieves exceptional performance while requiring minimal parameters and memory for fine-tuning large foundation models. Its general idea is to exploit the su...
We present a new adaptation method MaCP, Minimal yet Mighty adaptive Cosine Projection, that achieves exceptional performance while requiring minimal parameters and memory for fine-tuning large foundation models. Its general idea is to exploit the su...
The bidirectional steerability between different-size subsystems is discussed for a single parameter accelerated qubit-qutrit system. The decoherence due to the mixing and acceleration parameters is investigated, where for the total system and the qu...
Recent advances in theoretical atomic physics have enabled large-scale calculation of atomic parameters for a variety of atomic processes with high degree of precision. The development and application of these methods is the aim of the Iron Project...
Large language models (LLMs) have demonstrated remarkable performance and tremendous potential across a wide range of tasks. However, deploying these models has been challenging due to the astronomical amount of model parameters, which requires a dem...
The statistical analysis of gathered of astronomical objects (such as open cluster) are excellent tools to compute its parameters and to constrain the theory of its evolution. Here, we are represented detailed structural and membership analysis of an...
This paper establishes a link between endowments, patience types, and the parameters of the HARA Bernoulli utility function that ensure equilibrium uniqueness in an economy with two goods and two impatience types with additive separable preferences....
Understanding the influence of dipolar interactions in magnetic hyperthermia (MH) experiments is of crucial importance for a fine optimization of nanoparticle (NP) heating power. In this study, we use a kinetic Monte-Carlo algorithm to calculate hyst...
The MIST experiment aims to detect the cosmological 21-cm signal through sky observations at 25-125 MHz using a wide-beam antenna. The antenna is mounted above the soil and the beam characteristics are highly dependent on the soil's electrical proper...
We provide a comprehensive comparison of linear amplifiers and microwave photon-counters in axion dark matter experiments. The study is done assuming a range of realistic operating conditions and detector parameters, over the frequency range between...
Noise injection (NI) is an efficient technique to mitigate over-fitting in neural networks (NNs). The Bernoulli NI procedure as implemented in dropout and shakeout has connections with $l_1$ and $l_2$ regularization for the NN model parameters. We pr...
We consider random hyperbolic graphs in hyperbolic spaces of any dimension $d+1\geq 2$. We present a rescaling of model parameters that casts the random hyperbolic graph model of any dimension to a unified mathematical framework, leaving the degree d...
We explore an interesting connection between black hole shadow parameters and the acceleration bounds for radial linear uniformly accelerated (LUA) trajectories in static spherically symmetric black hole spacetime geometries of the Schwarzschild type...
By adding utm campaign parameters to the destination URLs you use in referral links and ad campaigns, you can view which campaigns refer traffic. When a user clicks a referral link, the URL …
In this paper, we combine communication-theoretic laws with known, practically verified results from circuit theory. As a result, we obtain closed-form theoretical expressions linking fundamental system design and environment parameters with the powe...
This paper investigates ultrafilters in the context of connectivity systems, defined as pairs $(X, f)$ where $X$ is a finite set and $f$ is a symmetric submodular function. Ultrafilters, essential in topology and set theory, are extended to these sys...
We use a sample of ~16,000 non-emission line galaxies from the SDSS to investigate the physical parameters underlying the well-known color-magnitude and color-sigma relations. Galaxies are sorted in terms of velocity dispersions (sigma), luminosity...
Lasso is a seminal contribution to high-dimensional statistics, but it hinges on a tuning parameter that is difficult to calibrate in practice. A partial remedy for this problem is Square-Root Lasso, because it inherently calibrates to the noise vari...
The TREX is a recently introduced approach to sparse linear regression. In contrast to most well-known approaches to penalized regression, the TREX can be formulated without the use of tuning parameters. In this paper, we establish the first known pr...
High precision assembly of mechanical parts requires accuracy exceeding the robot precision. Conventional part mating methods used in the current manufacturing requires tedious tuning of numerous parameters before deployment. We show how the robot ca...