Related papers: Expected Limits on R-symmetric $\mu \to e $ Proces…

Mrs. Gerber's Lemma lower bounds the entropy at the output of a binary symmetric channel in terms of the entropy of the input process. In this paper, we lower bound the output entropy via a different measure of input uncertainty, pertaining…

We obtain limits on the electromagnetic and weak dipole moments of the tau-lepton in the framework of a Left-Right symmetric model (LRSM) and a class of $E_6$ inspired models with an additional neutral vector boson $Z_\theta$. Using as an…

Mixed linear regression (MLR) model is among the most exemplary statistical tools for modeling non-linear distributions using a mixture of linear models. When the additive noise in MLR model is Gaussian, Expectation-Maximization (EM)…

This paper investigates the optimal ergodic sublinear convergence rate of the relaxed proximal point algorithm for solving monotone variational inequality problems. The exact worst case convergence rate is computed using the performance…

We re-examine the parameter space of the constrained minimal supersymmetric extension of the Standard Model (CMSSM), taking account of the restricted range of \Omega_{CDM} h^2 consistent with the WMAP data. This provides a significantly…

The sum of radii problem ($k$-MSR) asks, given a metric space on $n$ points, to place $k$ balls covering all points so as to minimize the sum of their radii. Despite extensive study from the perspectives of approximation and parameterized…

We examine codes, over the additive Gaussian noise channel, designed for reliable communication at some specific signal-to-noise ratio (SNR) and constrained by the permitted minimum mean-square error (MMSE) at lower SNRs. The maximum…

The flavor violating $\mu^--e^-$ conversion in nuclei is studied within the minimal supersymmetric standard model. We focus on the R-parity violating contributions at tree level including the trilinear and the bilinear terms in the…

The Expectation Maximisation (EM) algorithm is widely used to optimise non-convex likelihood functions with latent variables. Many authors modified its simple design to fit more specific situations. For instance, the Expectation (E) step…

The softmax-contaminated mixture of experts (MoE) model is deployed when a large-scale pre-trained model, which plays the role of a fixed expert, is fine-tuned for learning downstream tasks by including a new contamination part, or prompt,…

Threshold and ambiguity phenomena are studied in Part 1 of this work where approximations for the mean-squared-error (MSE) of the maximum likelihood estimator are proposed using the method of interval estimation (MIE), and where approximate…

Inspired by the recent experimental results which show deviations from the standard model (SM) predictions of $b\rightarrow s \ell^+\ell^-$ transitions, we study the $R$-parity violating minimal supersymmetric standard model (RPV-MSSM)…

We derive an asymptotic expansion for the log likelihood of Gaussian mixture models (GMMs) with equal covariance matrices in the low signal-to-noise regime. The expansion reveals an intimate connection between two types of algorithms for…

For a metric $\mu$ on a finite set $T$, the minimum 0-extension problem 0-Ext$[\mu]$ is defined as follows: Given $V\supseteq T$ and $\ c:{V \choose 2}\rightarrow \mathbf{Q_+}$, minimize $\sum c(xy)\mu(\gamma(x),\gamma(y))$ subject to…

Mixture of Experts (MoE) are successful models for modeling heterogeneous data in many statistical learning problems including regression, clustering and classification. Generally fitted by maximum likelihood estimation via the well-known…

We analyze the one loop correction to $Z\rightarrow \nu\nu$ decay in framework of Minimal R-symmetric Supersymmetric Standard Model(MRSSM) in detail with normal and inverse neutrino mass orderings, as a function of $\tan\beta$, Dirac mass…

The minimum error entropy (MEE) criterion has been successfully used in fields such as parameter estimation, system identification and the supervised machine learning. There is in general no explicit expression for the optimal MEE estimate…

DELPHI data collected at centre-of-mass energies up to 208 GeV have been analysed to search for charginos, neutralinos and sfermions in the framework of the Minimal Supersymmetric Standard Model (MSSM) with R-parity conservation. No…

We re-examine the bounds on supersymmetric particle masses in light of the new E821 data on the muon anomalous magnetic moment and the revised theoretical calculations of its hadronic contributions. The current experimental excess is either…

This paper presents a lower bound for optimizing a finite sum of $n$ functions, where each function is $L$-smooth and the sum is $\mu$-strongly convex. We show that no algorithm can reach an error $\epsilon$ in minimizing all functions from…